Study on a resource allocation scheme in multi-hop MIMO-OFDM systems over lognormal-rayleigh compound channels

Directory of Open Access Journals (Sweden)

LIU Jun

2015-10-01

Full Text Available For new generation wireless communication networks,this paper studies the optimization of the capacity and end-to-end throughput of the MIMO-OFDM based multi-hop relay systems.A water-filling power allocation method is proposed to improve the channel capacity and the throughput of the MIMO-OFDM system based multi-hop relay system in the Lognormal-Rayleigh shadowing compound channels.Simulations on the capacity and throughput show that the water-filling algorithm can improve the system throughput effectively in the MIMO-OFDM multi-hop relay system.

Performance Analysis of RF-FSO Multi-Hop Networks

KAUST Repository

Makki, Behrooz

2017-05-12

We study the performance of multi-hop networks composed of millimeter wave (MMW)-based radio frequency (RF) and free-space optical (FSO) links. The results are obtained in the cases with and without hybrid automatic repeat request (HARQ). Taking the MMW characteristics of the RF links into account, we derive closed-form expressions for the network outage probability. We also evaluate the effect of various parameters such as power amplifiers efficiency, number of antennas as well as different coherence times of the RF and the FSO links on the system performance. Finally, we present mappings between the performance of RF- FSO multi-hop networks and the ones using only the RF- or the FSO-based communication, in the sense that with appropriate parameter settings the same outage probability is achieved in these setups. The results show the efficiency of the RF-FSO setups in different conditions. Moreover, the HARQ can effectively improve the outage probability/energy efficiency, and compensate the effect of hardware impairments in RF-FSO networks. For common parameter settings of the RF-FSO dual- hop networks, outage probability 10^{-4} and code rate 3 nats-per-channel-use, the implementation of HARQ with a maximum of 2 and 3 retransmissions reduces the required power, compared to the cases with no HARQ, by 13 and 17 dB, respectively.

Multi-hop Relaying: An End-to-End Delay Analysis

KAUST Repository

Chaaban, Anas

2015-12-01

The impact of multi-hopping schemes on the communication latency in a relay channel is studied. The main aim is to characterize conditions under which such schemes decrease the communication latency given a reliability requirement. Both decode-forward (DF) and amplify-forward (AF) with block coding are considered, and are compared with the point-to-point (P2P) scheme which ignores the relay. Latency expressions for the three schemes are derived, and conditions under which DF and AF reduce latency are obtained for high signal-to-noise ratio (SNR). Interestingly, these conditions are more strict when compared to the conditions under which the same multi-hopping schemes achieve higher long-term (information-theoretic) rates than P2P. It turns out that the relation between the sourcedestination SNR and the harmonic mean of the SNR’s of the channels to and from the relay dictates whether multi-hopping reduces latency or not.

Cascading Multi-Hop Reservation and Transmission in Underwater Acoustic Sensor Networks

Directory of Open Access Journals (Sweden)

Jae-Won Lee

2014-10-01

Full Text Available The long propagation delay in an underwater acoustic channel makes designing an underwater media access control (MAC protocol more challenging. In particular, handshaking-based MAC protocols widely used in terrestrial radio channels have been known to be inappropriate in underwater acoustic channels, because of the inordinately large latency involved in exchanging control packets. Furthermore, in the case of multi-hop relaying in a hop-by-hop handshaking manner, the end-to-end delay significantly increases. In this paper, we propose a new MAC protocol named cascading multi-hop reservation and transmission (CMRT. In CMRT, intermediate nodes between a source and a destination may start handshaking in advance for the next-hop relaying before handshaking for the previous node is completed. By this concurrent relaying, control packet exchange and data delivery cascade down to the destination. In addition, to improve channel utilization, CMRT adopts a packet-train method where multiple data packets are sent together by handshaking once. Thus, CMRT reduces the time taken for control packet exchange and accordingly increases the throughput. The performance of CMRT is evaluated and compared with that of two conventional MAC protocols (multiple-access collision avoidance for underwater (MACA-U and MACA-U with packet trains (MACA-UPT. The results show that CMRT outperforms other MAC protocols in terms of both throughput and end-to-end delay.

A Stochastic Geometry Model for Multi-hop Highway Vehicular Communication

KAUST Repository

Farooq, Muhammad Junaid

2015-11-19

Carrier sense multiple access (CSMA) protocol is standardized for vehicular communication to ensure a distributed and efficient communication between vehicles. However, several vehicular applications require efficient multi-hop information dissemination. This paper exploits stochastic geometry to develop a tractable and accurate modeling framework to characterize the multi-hop transmissions for vehicular networks in a multi-lane highway setup. In particular, we study the tradeoffs between per-hop packet forward progress, per-hop transmission success probability, and spatial frequency reuse (SFR) efficiency imposed by different packet forwarding schemes, namely, most forward with fixed radius (MFR), the nearest with forward progress (NFP), and the random with forward progress (RFP). We also define a new performance metric, denoted as the aggregate packet progress (APP), which is a dimensionless quantity that captures the aforementioned tradeoffs. To this end, the developed model reveals the interplay between the spectrum sensing threshold (th) of the CSMA protocol and the packet forwarding scheme. Our results show that, in contrary to ALOHA networks which always favor NFP, MFR may achieve the highest APP in CSMA networks if th is properly chosen.

On the Performance of Millimeter Wave-based RF-FSO Multi-hop and Mesh Networks

KAUST Repository

Makki, Behrooz

2017-09-22

This paper studies the performance of multi-hop and mesh networks composed of millimeter wave-based radio frequency (RF) and free-space optical (FSO) links. The results are obtained in cases with and without hybrid automatic repeat request (HARQ). Using the central limit theorem as well as other state-of-the-art approximation schemes, we derive closed-form expressions for the networks’ outage probability and ergodic achievable rates. We also evaluate the effect of various parameters such as power amplifiers efficiency, number of antennas as well as different coherence times of the RF and the FSO links on the system performance. Finally, we determine the minimum number of the transmit antennas in the RF link such that the same rate is supported in the RF- and the FSO-based hops. The results show the efficiency of the RF-FSO setups in different conditions. Moreover, HARQ can effectively improve the outage probability/energy efficiency, and compensate for the effect of hardware impairments in RF-FSO networks. For common parameter settings of the RF-FSO dual-hop networks, outage probability of 10−4 and code rate of 3 nats-per-channel-use, the implementation of HARQ with a maximum of 2 and 3 retransmissions reduces the required power, compared to cases with open-loop communication, by 13 and 17 dB, respectively.

Link and route availability for Inter-working multi-hop wireless networks

CSIR Research Space (South Africa)

Salami, O

2009-09-01

Full Text Available pairs in inter-working multi-hop wireless networks can be evaluated based on the availability and reliability of radio links that form the communication path linking the nodes. This paper presents an analytical study of the link and route availability...

A Stochastic Geometry Model for Multi-hop Highway Vehicular Communication

KAUST Repository

Farooq, Muhammad Junaid; Elsawy, Hesham; Alouini, Mohamed-Slim

2015-01-01

dissemination. This paper exploits stochastic geometry to develop a tractable and accurate modeling framework to characterize the multi-hop transmissions for vehicular networks in a multi-lane highway setup. In particular, we study the tradeoffs between per

MCBT: Multi-Hop Cluster Based Stable Backbone Trees for Data Collection and Dissemination in WSNs

Directory of Open Access Journals (Sweden)

Tae-Jin Lee

2009-07-01

Full Text Available We propose a stable backbone tree construction algorithm using multi-hop clusters for wireless sensor networks (WSNs. The hierarchical cluster structure has advantages in data fusion and aggregation. Energy consumption can be decreased by managing nodes with cluster heads. Backbone nodes, which are responsible for performing and managing multi-hop communication, can reduce the communication overhead such as control traffic and minimize the number of active nodes. Previous backbone construction algorithms, such as Hierarchical Cluster-based Data Dissemination (HCDD and Multicluster, Mobile, Multimedia radio network (MMM, consume energy quickly. They are designed without regard to appropriate factors such as residual energy and degree (the number of connections or edges to other nodes of a node for WSNs. Thus, the network is quickly disconnected or has to reconstruct a backbone. We propose a distributed algorithm to create a stable backbone by selecting the nodes with higher energy or degree as the cluster heads. This increases the overall network lifetime. Moreover, the proposed method balances energy consumption by distributing the traffic load among nodes around the cluster head. In the simulation, the proposed scheme outperforms previous clustering schemes in terms of the average and the standard deviation of residual energy or degree of backbone nodes, the average residual energy of backbone nodes after disseminating the sensed data, and the network lifetime.

Wifi, WiMax and LTE multi-hop mesh networks basic communication protocols and application areas

CERN Document Server

Wei, Hung-Yu; Dixit, Sudhir

2013-01-01

Wifi, WiMAX, and Cellular Multihop Networks presents an overview of WiFi-based and WiMAX-based multihop relay networks. As the first text to cover IEEE 802.16j multihop hop relay technology, this revolutionary resource explores the latest advances in multi-hop and ad-hoc networking. Not only does this reference provide the technological aspects, but also the applications for the emerging technology and architectural issues. Ranging from introductory material to advanced topics, this guidebook, plus PowerPoint slides, is essential for engineers, researchers, and students interested in

Multi-hop Relaying: An End-to-End Delay Analysis

KAUST Repository

Chaaban, Anas; Sezgin, Aydin

2015-01-01

The impact of multi-hopping schemes on the communication latency in a relay channel is studied. The main aim is to characterize conditions under which such schemes decrease the communication latency given a reliability requirement. Both decode

Analysis and Relative Evaluation of Connectivity of a Mobile Multi-Hop Network

Science.gov (United States)

Nakano, Keisuke; Miyakita, Kazuyuki; Sengoku, Masakazu; Shinoda, Shoji

In mobile multi-hop networks, a source node S and a destination node D sometimes encounter a situation where there is no multi-hop path between them when a message M, destined for D, arrives at S. In this situation, we cannot send M from S to D immediately; however, we can deliver M to D after waiting some time with the help of two capabilities of mobility. One of the capabilities is to construct a connected multi-hop path by changing the topology of the network during the waiting time (Capability 1), and the other is to move M closer to D during the waiting time (Capability 2). In this paper, we consider three methods to deliver M from S to D by using these capabilities in different ways. Method 1 uses Capability 1 and sends M from S to D after waiting until a connected multi-hop path appears between S and D. Method 2 uses Capability 2 and delivers M to D by allowing a mobile node to carry M from S to D. Method 3 is a combination of Methods 1 and 2 and minimizes the waiting time. We evaluate and compare these three methods in terms of the mean waiting time, from the time when M arrives at S to the time when D starts receiving M, as a new approach to connectivity evaluation. We consider a one-dimensional mobile multi-hop network consisting of mobile nodes flowing in opposite directions along a street. First, we derive some approximate equations and propose an estimation method to compute the mean waiting time of Method 1. Second, we theoretically analyze the mean waiting time of Method 2, and compute a lower bound of that of Method 3. By comparing the three methods under the same assumptions using results of the analyses and some simulation results, we show relations between the mean waiting times of these methods and show how Capabilities 1 and 2 differently affect the mean waiting time.

Interference Information Based Power Control for Cognitive Radio with Multi-Hop Cooperative Sensing

Science.gov (United States)

Yu, Youngjin; Murata, Hidekazu; Yamamoto, Koji; Yoshida, Susumu

Reliable detection of other radio systems is crucial for systems that share the same frequency band. In wireless communication channels, there is uncertainty in the received signal level due to multipath fading and shadowing. Cooperative sensing techniques in which radio stations share their sensing information can improve the detection probability of other systems. In this paper, a new cooperative sensing scheme that reduces the false detection probability while maintaining the outage probability of other systems is investigated. In the proposed system, sensing information is collected using multi-hop transmission from all sensing stations that detect other systems, and transmission decisions are based on the received sensing information. The proposed system also controls the transmit power based on the received CINRs from the sensing stations. Simulation results reveal that the proposed system can reduce the outage probability of other systems, or improve its link success probability.

Security for multi-hop wireless networks

CERN Document Server

Mahmoud, Mohamed M E A

2014-01-01

This Springer Brief discusses efficient security protocols and schemes for multi-hop wireless networks. It presents an overview of security requirements for these networks, explores challenges in securing networks and presents system models. The authors introduce mechanisms to reduce the overhead and identify malicious nodes that drop packets intentionally. Also included is a new, efficient cooperation incentive scheme to stimulate the selfish nodes to relay information packets and enforce fairness. Many examples are provided, along with predictions for future directions of the field. Security

Wireless multi-hop networks with stealing : large buffer asymptotics

NARCIS (Netherlands)

Guillemin, F.; Knessl, C.; Leeuwaarden, van J.S.H.

2010-01-01

Wireless networks equipped with CSMA are scheduled in a fully distributed manner. A disadvantage of such distributed control in multi-hop networks is the hidden node problem that causes the effect of stealing, in which a downstream node steals the channel from an upstream node with probability p.

Hop-by-HopWorm Propagation with Carryover Epidemic Model in Mobile Sensor Networks

Directory of Open Access Journals (Sweden)

Jun-Won Ho

2015-10-01

Full Text Available In the internet, a worm is usually propagated in a random multi-hop contact manner. However, the attacker will not likely select this random multi-hop propagation approach in a mobile sensor network. This is because multi-hop worm route paths to random vulnerable targets can be often breached due to node mobility, leading to failure of fast worm spread under this strategy. Therefore, an appropriate propagation strategy is needed for mobile sensor worms. To meet this need, we discuss a hop-by-hop worm propagation model in mobile sensor networks. In a hop-by-hop worm propagation model, benign nodes are infected by worm in neighbor-to-neighbor spread manner. Since worm infection occurs in hop-by-hop contact, it is not substantially affected by a route breach incurred by node mobility. We also propose the carryover epidemic model to deal with the worm infection quota deficiency that might occur when employing an epidemic model in a mobile sensor network. We analyze worm infection capability under the carryover epidemic model. Moreover, we simulate hop-by-hop worm propagation with carryover epidemic model by using an ns-2 simulator. The simulation results demonstrate that infection quota carryovers are seldom observed where a node’s maximum speed is no less than 20 m/s.

Project Based Learning in Multi-Grade Class

Science.gov (United States)

Ciftci, Sabahattin; Baykan, Ayse Aysun

2013-01-01

The purpose of this study is to evaluate project based learning in multi-grade classes. This study, based on a student-centered learning approach, aims to analyze students' and parents' interpretations. The study was done in a primary village school belonging to the Centre of Batman, already adapting multi-grade classes in their education system,…

Cross-layer optimization of wireless multi-hop networks

OpenAIRE

Soldati, Pablo

2007-01-01

The interest in wireless communications has grown constantly for the past decades, leading to an enormous number of applications and services embraced by billions of users. In order to meet the increasing demand for mobile Internet access, several high data-rate radio networking technologies have been proposed to offer wide area high-speed wireless communications, eventually replacing fixed (wired) networks for many applications. This thesis considers cross-layer optimization of multi-hop rad...

Multi-hop amplify-and-forward relaying cooperation in the presence of I/Q imbalance

KAUST Repository

Qi, Jian; Aï ssa, Sonia; Alouini, Mohamed-Slim

2013-01-01

In this paper, multi-hop cooperative networks implementing channel state information (CSI)-assisted amplify-and-forward (AF) relaying in the presence of in-phase and quadrature-phase (I/Q) imbalance are investigated. We propose a compensation algorithm for the I/Q imbalance. The performance of the multi-hop CSI-assisted AF cooperative networks with and without compensation for I/Q imbalance in Nakagami-m fading environment is evaluated in terms of average symbol error probability. Numerical results are provided and show that the proposed compensation method can effectively mitigate the impact of I/Q imbalance. © 2013 IEEE.

Multi-hop amplify-and-forward relaying cooperation in the presence of I/Q imbalance

KAUST Repository

Qi, Jian

2013-06-01

In this paper, multi-hop cooperative networks implementing channel state information (CSI)-assisted amplify-and-forward (AF) relaying in the presence of in-phase and quadrature-phase (I/Q) imbalance are investigated. We propose a compensation algorithm for the I/Q imbalance. The performance of the multi-hop CSI-assisted AF cooperative networks with and without compensation for I/Q imbalance in Nakagami-m fading environment is evaluated in terms of average symbol error probability. Numerical results are provided and show that the proposed compensation method can effectively mitigate the impact of I/Q imbalance. © 2013 IEEE.

Polish Hip Hop as a Form of Multiliteracies and Situated Learning

Science.gov (United States)

Torrence, Michael L.

2009-01-01

The purpose of this ethnographic study was to examine Hip Hop in Poland through the lens of multiliteracies and situated learning. This analysis is concerned with the transmission of Hip Hop to and within Wroclaw, Poland, and its acculturation and assimilation in Wroclaw, Poland. Further, this study seeks to illustrate how professional Polish Hip…

Analysis of route availability in inter-working multi-hop wireless networks

CSIR Research Space (South Africa)

Salami, O

2009-07-01

Full Text Available In order to link a source-destination node pair in inter-working multi-hop wireless networks, links or routes must first be available. It is only after establishing the availability of links and routes between nodes that factors which affect...

An implementation of traffic light system using multi-hop Ad hoc networks

KAUST Repository

Ansari, Imran Shafique

2009-08-01

In ad hoc networks nodes cooperate with each other to form a temporary network without the aid of any centralized administration. No wired base station or infrastructure is supported, and each host communicates via radio packets. Each host must act as a router, since routes are mostly multi-hop, due to the limited power transmission set by government agencies, (e.g. the Federal Communication Commission (FCC), which is 1 Watt in Industrial Scientific and Medical (ISM) band. The natures of wireless mobile ad hoc networks depend on batteries or other fatiguing means for their energy. A limited energy capacity may be the most significant performance constraint. Therefore, radio resource and power management is an important issue of any wireless network. In this paper, a design for traffic light system employing ad hoc networks is proposed. The traffic light system runs automatically based on signals sent through a multi-hop ad hoc network of \\'n\\' number of nodes utilizing the Token Ring protocol, which is efficient for this application from the energy prospective. The experiment consists of a graphical user interface that simulates the traffic lights and laptops (which have wireless network adapters) are used to run the graphical user interface and are responsible for setting up the ad hoc network between them. The traffic light system has been implemented utilizing A Mesh Driver (which allows for more than one wireless device to be connected simultaneously) and Java-based client-server programs. © 2009 IEEE.

An analytical model for the performance of geographical multi-hop broadcast

NARCIS (Netherlands)

Klein Wolterink, W.; Heijenk, G.; Berg, J.L. van den

2012-01-01

In this paper we present an analytical model accurately describing the behaviour of a multi-hop broadcast protocol. Our model covers the scenario in which a message is forwarded over a straight road and inter-node distances are distributed exponentially. Intermediate forwarders draw a small random

An implementation of traffic light system using multi-hop Ad hoc networks

KAUST Repository

Ansari, Imran Shafique

2009-01-01

as a router, since routes are mostly multi-hop, due to the limited power transmission set by government agencies, (e.g. the Federal Communication Commission (FCC), which is 1 Watt in Industrial Scientific and Medical (ISM) band. The natures of wireless

Adaptive Demand-Driven Multicast Routing in Multi-Hop Wireless Ad Hoc Networks

National Research Council Canada - National Science Library

Jetcheva, Jorjeta G

2004-01-01

...) nodes that wish to communicate. Each node in the ad hoc network acts as a router and forwards packets on behalf of other nodes, allowing nodes that are not within wireless range of each other to communicate over multi-hop paths...

Spatial reuse of wireless medium in multi-hop wireless sensor networks

NARCIS (Netherlands)

Geerlings, J.; Geerlings, J.; van Hoesel, L.F.W.; Hoeksema, F.W.; Slump, Cornelis H.; Havinga, Paul J.M.

2007-01-01

The idea of multi-hop communication originates from the 1990’s and is eagerly incorporated in the wireless sensor network research field, since a tremendous amount of energy can be saved by letting —often battery powered– nodes in the network assist each other in forwarding packets. In such systems

Cultivating the Spatial Politics of Community-Based Literacy Practices in Hip-Hop

Science.gov (United States)

Prier, Darius D.

2013-01-01

In this article, the social imagination of community-based sites of urban resistance enable out-of-school literacy practices in Black popular culture to foreground the contemporary context in which youth empowerment is nurtured in out-of-school learning settings. Second, the author chronicles how youth advocates in hip-hop--based community…

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks.

Science.gov (United States)

Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X

2015-12-26

Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Liu Yang

2015-12-01

Full Text Available Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs in the network act as routers to transmit data to base station (BS cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

Self-Organization Scheme for Balanced Routing in Large-Scale Multi-Hop Networks

DEFF Research Database (Denmark)

Badiu, Mihai Alin; Saad, David; Coon, Justin P.

2018-01-01

We propose a self-organization scheme for cost-effective and load-balanced routing in multi-hop networks. To avoid overloading nodes that provide favourable routing conditions, we assign each node with a cost function that penalizes high loads. Thus, finding routes to sink nodes is formulated...

Joint Scheduling for Dual-Hop Block-Fading Broadcast Channels

KAUST Repository

Zafar, Ammar

2012-09-16

In this paper, we propose joint user-and-hop scheduling over dual-hop block-fading broadcast channels in order to exploit multi-user diversity gains and multi-hop diversity gains all together. To achieve this objective, the first and second hops are scheduled opportunistically based on the channel state information and as a prerequisite we assume that the relay, which is half-duplex and operates using decode-and-forward, is capable of storing the received packets from the source until the channel condition of the destined user becomes good to be scheduled. We formulate the joint scheduling problem as maximizing the weighted sum of the long term achievable rates by the users under a stability constraint, which means that on the long term the rate received by the relay should equal the rate transmitted by it, in addition to constant or variable power constraints. We show that this problem is equivalent to a single-hop broadcast channel by treating the source as a virtual user with an optimal priority weight that maintains the stability constraint. We show how to obtain the source weight either off-line based on channel statistics or on real-time based on channel measurements. Furthermore, we consider special cases including the maximum sum rate scheduler and the proportional fair scheduler. We demonstrate via numerical results that our proposed joint scheduling scheme enlarges the rate region as compared with a scheme that employs multi-user scheduling alone.

Cross-Layer Scheme to Control Contention Window for Per-Flow in Asymmetric Multi-Hop Networks

Science.gov (United States)

Giang, Pham Thanh; Nakagawa, Kenji

The IEEE 802.11 MAC standard for wireless ad hoc networks adopts Binary Exponential Back-off (BEB) mechanism to resolve bandwidth contention between stations. BEB mechanism controls the bandwidth allocation for each station by choosing a back-off value from one to CW according to the uniform random distribution, where CW is the contention window size. However, in asymmetric multi-hop networks, some stations are disadvantaged in opportunity of access to the shared channel and may suffer severe throughput degradation when the traffic load is large. Then, the network performance is degraded in terms of throughput and fairness. In this paper, we propose a new cross-layer scheme aiming to solve the per-flow unfairness problem and achieve good throughput performance in IEEE 802.11 multi-hop ad hoc networks. Our cross-layer scheme collects useful information from the physical, MAC and link layers of own station. This information is used to determine the optimal Contention Window (CW) size for per-station fairness. We also use this information to adjust CW size for each flow in the station in order to achieve per-flow fairness. Performance of our cross-layer scheme is examined on various asymmetric multi-hop network topologies by using Network Simulator (NS-2).

Sampling Memories: Using Hip-Hop Aesthetics to Learn from Urban Schooling Experiences

Science.gov (United States)

Petchauer, Emery

2012-01-01

This article theorizes and charts the implementation of a learning activity designed from the hip-hop aesthetic of sampling. The purpose of this learning activity was to enable recent urban school graduates to reflect upon their previous schooling experiences as a platform for future learning in higher education. This article illustrates what…

Multi-View Multi-Instance Learning Based on Joint Sparse Representation and Multi-View Dictionary Learning.

Science.gov (United States)

Li, Bing; Yuan, Chunfeng; Xiong, Weihua; Hu, Weiming; Peng, Houwen; Ding, Xinmiao; Maybank, Steve

2017-12-01

In multi-instance learning (MIL), the relations among instances in a bag convey important contextual information in many applications. Previous studies on MIL either ignore such relations or simply model them with a fixed graph structure so that the overall performance inevitably degrades in complex environments. To address this problem, this paper proposes a novel multi-view multi-instance learning algorithm (MIL) that combines multiple context structures in a bag into a unified framework. The novel aspects are: (i) we propose a sparse -graph model that can generate different graphs with different parameters to represent various context relations in a bag, (ii) we propose a multi-view joint sparse representation that integrates these graphs into a unified framework for bag classification, and (iii) we propose a multi-view dictionary learning algorithm to obtain a multi-view graph dictionary that considers cues from all views simultaneously to improve the discrimination of the MIL. Experiments and analyses in many practical applications prove the effectiveness of the M IL.

You know what it is: learning words through listening to hip-hop.

Science.gov (United States)

Chesley, Paula

2011-01-01

Music listeners have difficulty correctly understanding and remembering song lyrics. However, results from the present study support the hypothesis that young adults can learn African-American English (AAE) vocabulary from listening to hip-hop music. Non-African-American participants first gave free-response definitions to AAE vocabulary items, after which they answered demographic questions as well as questions addressing their social networks, their musical preferences, and their knowledge of popular culture. Results from the survey show a positive association between the number of hip-hop artists listened to and AAE comprehension vocabulary scores. Additionally, participants were more likely to know an AAE vocabulary item if the hip-hop artists they listen to use the word in their song lyrics. Together, these results suggest that young adults can acquire vocabulary through exposure to hip-hop music, a finding relevant for research on vocabulary acquisition, the construction of adolescent and adult identities, and the adoption of lexical innovations.

You know what it is: learning words through listening to hip-hop.

Directory of Open Access Journals (Sweden)

Paula Chesley

Full Text Available Music listeners have difficulty correctly understanding and remembering song lyrics. However, results from the present study support the hypothesis that young adults can learn African-American English (AAE vocabulary from listening to hip-hop music. Non-African-American participants first gave free-response definitions to AAE vocabulary items, after which they answered demographic questions as well as questions addressing their social networks, their musical preferences, and their knowledge of popular culture. Results from the survey show a positive association between the number of hip-hop artists listened to and AAE comprehension vocabulary scores. Additionally, participants were more likely to know an AAE vocabulary item if the hip-hop artists they listen to use the word in their song lyrics. Together, these results suggest that young adults can acquire vocabulary through exposure to hip-hop music, a finding relevant for research on vocabulary acquisition, the construction of adolescent and adult identities, and the adoption of lexical innovations.

The Distribution of Minimum of Ratios of Two Random Variables and Its Application in Analysis of Multi-hop Systems

Directory of Open Access Journals (Sweden)

A. Stankovic

2012-12-01

Full Text Available The distributions of random variables are of interest in many areas of science. In this paper, ascertaining on the importance of multi-hop transmission in contemporary wireless communications systems operating over fading channels in the presence of cochannel interference, the probability density functions (PDFs of minimum of arbitrary number of ratios of Rayleigh, Rician, Nakagami-m, Weibull and α-µ random variables are derived. These expressions can be used to study the outage probability as an important multi-hop system performance measure. Various numerical results complement the proposed mathematical analysis.

Sleep/wake scheduling scheme for minimizing end-to-end delay in multi-hop wireless sensor networks

OpenAIRE

Madani Sajjad; Nazir Babar; Hasbullah Halabi

2011-01-01

Abstract We present a sleep/wake schedule protocol for minimizing end-to-end delay for event driven multi-hop wireless sensor networks. In contrast to generic sleep/wake scheduling schemes, our proposed algorithm performs scheduling that is dependent on traffic loads. Nodes adapt their sleep/wake schedule based on traffic loads in response to three important factors, (a) the distance of the node from the sink node, (b) the importance of the node's location from connectivity's perspective, and...

Engaging Black Males on Their Own Terms: What Schools Can Learn from Black Males Who Produce Hip-Hop

Science.gov (United States)

Irby, Decoteau J.; Petchauer, Emery; Kirkland, David

2013-01-01

Education scholars and practitioners have much to learn about engagement and motivation of Black males by directing their inquiries to more organic sites of hip-hop cultural production outside of schools. One such site is the hip-hop's informal labor economy where Black males engage in earning money through hip-hop cultural production. Labor…

Personalised learning object based on multi-agent model and learners’ learning styles

Directory of Open Access Journals (Sweden)

Noppamas Pukkhem

2011-09-01

Full Text Available A multi-agent model is proposed in which learning styles and a word analysis technique to create a learning object recommendation system are used. On the basis of a learning style-based design, a concept map combination model is proposed to filter out unsuitable learning concepts from a given course. Our learner model classifies learners into eight styles and implements compatible computational methods consisting of three recommendations: i non-personalised, ii preferred feature-based, and iii neighbour-based collaborative filtering. The analysis of preference error (PE was performed by comparing the actual preferred learning object with the predicted one. In our experiments, the feature-based recommendation algorithm has the fewest PE.

A feedback-retransmission based asynchronous frequency hopping MAC protocol for military aeronautical ad hoc networks

Directory of Open Access Journals (Sweden)

Jinhui TANG

2018-05-01

Full Text Available Attacking time-sensitive targets has rigid demands for the timeliness and reliability of information transmission, while typical Media Access Control (MAC designed for this application works well only in very light-load scenarios; as a consequence, the performances of system throughput and channel utilization are degraded. For this problem, a feedback-retransmission based asynchronous FRequency hopping Media Access (FRMA control protocol is proposed. Burst communication, asynchronous Frequency Hopping (FH, channel coding, and feedback retransmission are utilized in FRMA. With the mechanism of asynchronous FH, immediate packet transmission and multi-packet reception can be realized, and thus the timeliness is improved. Furthermore, reliability can be achieved via channel coding and feedback retransmission. With theories of queuing theory, Markov model, packets collision model, and discrete Laplace transformation, the formulas of packet success probability, system throughput, average packet end-to-end delay, and delay distribution are obtained. The approximation accuracy of theoretical derivation is verified by experimental results. Within a light-load network, the proposed FRMA has the ability of millisecond delay and 99% reliability as well as outperforms the non-feedback-retransmission based asynchronous frequency hopping media access control protocol. Keywords: Ad hoc networks, Aeronautical communications, Frequency hopping, Media Access Control (MAC, Time-sensitive

Backoff-stage synchronization in three-hop string-topology wireless networks with hidden nodes

Science.gov (United States)

Sanada, Kosuke; Sekiya, Hiroo; Komuro, Nobuyoshi; Sakata, Shiro

In IEEE 802.11 wireless multi-hop networks, each node works individually and their individual operations generate entire network dynamics. It is important to clarify the network dynamics in wireless multi-hop networks for designing and constructing multi-hop communication networks. This paper presents the network-dynamics investigations for three-hop string-topology wireless network in detail. From the investigations, a “backoff-stage synchronization” phenomenon, which is mutuality between hidden nodes, is found. The mechanism of the backoff-stage synchronization is expressed and the sufficient conditions for the synchronization occurrence are given. This phenomenon gives some impacts on the IEEE 802.11 multi-hop-network communications.

Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

Science.gov (United States)

Shi, Jun; Liu, Xiao; Li, Yan; Zhang, Qi; Li, Yingjie; Ying, Shihui

2015-10-30

Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state-of-the-art unsupervised feature learning method suitable for EEG feature representation. Collaborative representation (CR) is an effective data coding method used as a classifier. Here we use CR as a data representation method to learn features from the EEG signal. A joint collaboration model is established to develop a multi-view learning algorithm, and generate joint CR (JCR) codes to fuse and represent multi-channel EEG signals. A two-stage multi-view learning-based sleep staging framework is then constructed, in which JCR and joint sparse representation (JSR) algorithms first fuse and learning the feature representation from multi-channel EEG signals, respectively. Multi-view JCR and JSR features are then integrated and sleep stages recognized by a multiple kernel extreme learning machine (MK-ELM) algorithm with grid search. The proposed two-stage multi-view learning algorithm achieves superior performance for sleep staging. With a K-means clustering based dictionary, the mean classification accuracy, sensitivity and specificity are 81.10 ± 0.15%, 71.42 ± 0.66% and 94.57 ± 0.07%, respectively; while with the dictionary learned using the submodular optimization method, they are 80.29 ± 0.22%, 71.26 ± 0.78% and 94.38 ± 0.10%, respectively. The two-stage multi-view learning based sleep staging framework outperforms all other classification methods compared in this work, while JCR is superior to JSR. The proposed multi-view learning framework has the potential for sleep staging based on multi-channel or multi-modality polysomnography signals. Copyright © 2015 Elsevier B.V. All rights reserved.

Improving Multi-Instance Multi-Label Learning by Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Ying Yin

2016-05-01

Full Text Available Multi-instance multi-label learning is a learning framework, where every object is represented by a bag of instances and associated with multiple labels simultaneously. The existing degeneration strategy-based methods often suffer from some common drawbacks: (1 the user-specific parameter for the number of clusters may incur the effective problem; (2 SVM may bring a high computational cost when utilized as the classifier builder. In this paper, we propose an algorithm, namely multi-instance multi-label (MIML-extreme learning machine (ELM, to address the problems. To our best knowledge, we are the first to utilize ELM in the MIML problem and to conduct the comparison of ELM and SVM on MIML. Extensive experiments have been conducted on real datasets and synthetic datasets. The results show that MIMLELM tends to achieve better generalization performance at a higher learning speed.

Scaffold hopping in drug discovery using inductive logic programming.

Science.gov (United States)

Tsunoyama, Kazuhisa; Amini, Ata; Sternberg, Michael J E; Muggleton, Stephen H

2008-05-01

In chemoinformatics, searching for compounds which are structurally diverse and share a biological activity is called scaffold hopping. Scaffold hopping is important since it can be used to obtain alternative structures when the compound under development has unexpected side-effects. Pharmaceutical companies use scaffold hopping when they wish to circumvent prior patents for targets of interest. We propose a new method for scaffold hopping using inductive logic programming (ILP). ILP uses the observed spatial relationships between pharmacophore types in pretested active and inactive compounds and learns human-readable rules describing the diverse structures of active compounds. The ILP-based scaffold hopping method is compared to two previous algorithms (chemically advanced template search, CATS, and CATS3D) on 10 data sets with diverse scaffolds. The comparison shows that the ILP-based method is significantly better than random selection while the other two algorithms are not. In addition, the ILP-based method retrieves new active scaffolds which were not found by CATS and CATS3D. The results show that the ILP-based method is at least as good as the other methods in this study. ILP produces human-readable rules, which makes it possible to identify the three-dimensional features that lead to scaffold hopping. A minor variant of a rule learnt by ILP for scaffold hopping was subsequently found to cover an inhibitor identified by an independent study. This provides a successful result in a blind trial of the effectiveness of ILP to generate rules for scaffold hopping. We conclude that ILP provides a valuable new approach for scaffold hopping.

I Feel What He Was Doin': Responding to Justice-Oriented Teaching through Hip-Hop Aesthetics

Science.gov (United States)

Petchauer, Emery

2011-01-01

This study illustrates a set of learning activities designed from two hip-hop aesthetics and explores their use among a classroom of African American preservice teachers who graduated from urban school districts. Based on the two hip-hop aesthetics of kinetic consumption and autonomy/distance, the specific goal of these learning activities is to…

IMHRP: Improved Multi-Hop Routing Protocol for Wireless Sensor Networks

Science.gov (United States)

Huang, Jianhua; Ruan, Danwei; Hong, Yadong; Zhao, Ziming; Zheng, Hong

2017-10-01

Wireless sensor network (WSN) is a self-organizing system formed by a large number of low-cost sensor nodes through wireless communication. Sensor nodes collect environmental information and transmit it to the base station (BS). Sensor nodes usually have very limited battery energy. The batteries cannot be charged or replaced. Therefore, it is necessary to design an energy efficient routing protocol to maximize the network lifetime. This paper presents an improved multi-hop routing protocol (IMHRP) for homogeneous networks. In the IMHRP protocol, based on the distances to the BS, the CH nodes are divided into internal CH nodes and external CH nodes. The set-up phase of the protocol is based on the LEACH protocol and the minimum distance between CH nodes are limited to a special constant distance, so a more uniform distribution of CH nodes is achieved. In the steady-state phase, the routes of different CH nodes are created on the basis of the distances between the CH nodes. The energy efficiency of communication can be maximized. The simulation results show that the proposed algorithm can more effectively reduce the energy consumption of each round and prolong the network lifetime compared with LEACH protocol and MHT protocol.

Analysis of Probability of Non-zero Secrecy Capacity for Multi-hop Networks in Presence of Hardware Impairments over Nakagami-m Fading Channels

Directory of Open Access Journals (Sweden)

T.-T. Phu

2016-12-01

Full Text Available In this paper, we evaluate probability of non-zero secrecy capacity of multi-hop relay networks over Nakagami-m fading channels in presence of hardware impairments. In the considered protocol, a source attempts to transmit its data to a destination by using multi-hop randomize-and-forward (RF strategy. The data transmitted by the source and relays are overheard by an eavesdropper. For performance evaluation, we derive exact expressions of probability of non-zero secrecy capacity (PoNSC, which are expressed by sums of infinite series of exponential functions and exponential integral functions. We then perform Monte Carlo simulations to verify the theoretical analysis.

Stochastic Learning of Multi-Instance Dictionary for Earth Mover's Distance based Histogram Comparison

OpenAIRE

Fan, Jihong; Liang, Ru-Ze

2016-01-01

Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover's distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However, up to now, there is no existing multi-instance dictionary learning methods designed for EMD based histogram comparison. To fill this gap, we develop the first EMD-optimal dictionary learning method using stochastic optimization method. In the stoc...

Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs.

Science.gov (United States)

Javaid, Nadeem; Ahmed, Farwa; Wadud, Zahid; Alrajeh, Nabil; Alabed, Mohamad Souheil; Ilahi, Manzoor

2017-08-01

Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network.

Semi-Supervised Multi-View Ensemble Learning Based On Extracting Cross-View Correlation

Directory of Open Access Journals (Sweden)

ZALL, R.

2016-05-01

Full Text Available Correlated information between different views incorporate useful for learning in multi view data. Canonical correlation analysis (CCA plays important role to extract these information. However, CCA only extracts the correlated information between paired data and cannot preserve correlated information between within-class samples. In this paper, we propose a two-view semi-supervised learning method called semi-supervised random correlation ensemble base on spectral clustering (SS_RCE. SS_RCE uses a multi-view method based on spectral clustering which takes advantage of discriminative information in multiple views to estimate labeling information of unlabeled samples. In order to enhance discriminative power of CCA features, we incorporate the labeling information of both unlabeled and labeled samples into CCA. Then, we use random correlation between within-class samples from cross view to extract diverse correlated features for training component classifiers. Furthermore, we extend a general model namely SSMV_RCE to construct ensemble method to tackle semi-supervised learning in the presence of multiple views. Finally, we compare the proposed methods with existing multi-view feature extraction methods using multi-view semi-supervised ensembles. Experimental results on various multi-view data sets are presented to demonstrate the effectiveness of the proposed methods.

A novel communication mechanism based on node potential multi-path routing

Science.gov (United States)

Bu, Youjun; Zhang, Chuanhao; Jiang, YiMing; Zhang, Zhen

2016-10-01

With the network scales rapidly and new network applications emerge frequently, bandwidth supply for today's Internet could not catch up with the rapid increasing requirements. Unfortunately, irrational using of network sources makes things worse. Actual network deploys single-next-hop optimization paths for data transmission, but such "best effort" model leads to the imbalance use of network resources and usually leads to local congestion. On the other hand Multi-path routing can use the aggregation bandwidth of multi paths efficiently and improve the robustness of network, security, load balancing and quality of service. As a result, multi-path has attracted much attention in the routing and switching research fields and many important ideas and solutions have been proposed. This paper focuses on implementing the parallel transmission of multi next-hop data, balancing the network traffic and reducing the congestion. It aimed at exploring the key technologies of the multi-path communication network, which could provide a feasible academic support for subsequent applications of multi-path communication networking. It proposed a novel multi-path algorithm based on node potential in the network. And the algorithm can fully use of the network link resource and effectively balance network link resource utilization.

Brain Emotional Learning Based Intelligent Decoupler for Nonlinear Multi-Input Multi-Output Distillation Columns

Directory of Open Access Journals (Sweden)

M. H. El-Saify

2017-01-01

Full Text Available The distillation process is vital in many fields of chemical industries, such as the two-coupled distillation columns that are usually highly nonlinear Multi-Input Multi-Output (MIMO coupled processes. The control of MIMO process is usually implemented via a decentralized approach using a set of Single-Input Single-Output (SISO loop controllers. Decoupling the MIMO process into group of single loops requires proper input-output pairing and development of decoupling compensator unit. This paper proposes a novel intelligent decoupling approach for MIMO processes based on new MIMO brain emotional learning architecture. A MIMO architecture of Brain Emotional Learning Based Intelligent Controller (BELBIC is developed and applied as a decoupler for 4 input/4 output highly nonlinear coupled distillation columns process. Moreover, the performance of the proposed Brain Emotional Learning Based Intelligent Decoupler (BELBID is enhanced using Particle Swarm Optimization (PSO technique. The performance is compared with the PSO optimized steady state decoupling compensation matrix. Mathematical models of the distillation columns and the decouplers are built and tested in simulation environment by applying the same inputs. The results prove remarkable success of the BELBID in minimizing the loops interactions without degrading the output that every input has been paired with.

Framing and Reviewing Hip-Hop Educational Research

Science.gov (United States)

Petchauer, Emery

2009-01-01

Hip-hop has become relevant to the field of education because of its implications for understanding language, learning, identity, curriculum, and other areas. This integrative review provides historical context and cohesion for the burgeoning and discursive body of hip-hop scholarship by framing it according to three heuristic categories and…

Stochastic learning of multi-instance dictionary for earth mover’s distance-based histogram comparison

KAUST Repository

Fan, Jihong

2016-09-17

Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover’s distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However, up to now, there is no existing multi-instance dictionary learning methods designed for EMD-based histogram comparison. To fill this gap, we develop the first EMD-optimal dictionary learning method using stochastic optimization method. In the stochastic learning framework, we have one triplet of bags, including one basic bag, one positive bag, and one negative bag. These bags are mapped to histograms using a multi-instance dictionary. We argue that the EMD between the basic histogram and the positive histogram should be smaller than that between the basic histogram and the negative histogram. Base on this condition, we design a hinge loss. By minimizing this hinge loss and some regularization terms of the dictionary, we update the dictionary instances. The experiments over multi-instance retrieval applications shows its effectiveness when compared to other dictionary learning methods over the problems of medical image retrieval and natural language relation classification. © 2016 The Natural Computing Applications Forum

A deep learning-based multi-model ensemble method for cancer prediction.

Science.gov (United States)

Xiao, Yawen; Wu, Jun; Lin, Zongli; Zhao, Xiaodong

2018-01-01

Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged in recent years, progress in cancer prediction has been increasingly made based on gene expression, providing insight into effective and accurate treatment decision making. Thus, developing machine learning methods, which can successfully distinguish cancer patients from healthy persons, is of great current interest. However, among the classification methods applied to cancer prediction so far, no one method outperforms all the others. In this paper, we demonstrate a new strategy, which applies deep learning to an ensemble approach that incorporates multiple different machine learning models. We supply informative gene data selected by differential gene expression analysis to five different classification models. Then, a deep learning method is employed to ensemble the outputs of the five classifiers. The proposed deep learning-based multi-model ensemble method was tested on three public RNA-seq data sets of three kinds of cancers, Lung Adenocarcinoma, Stomach Adenocarcinoma and Breast Invasive Carcinoma. The test results indicate that it increases the prediction accuracy of cancer for all the tested RNA-seq data sets as compared to using a single classifier or the majority voting algorithm. By taking full advantage of different classifiers, the proposed deep learning-based multi-model ensemble method is shown to be accurate and effective for cancer prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

A Unified NET-MAC-PHY Cross-layer Framework for Performance Evaluation of Multi-hop Ad hoc WLANs

Directory of Open Access Journals (Sweden)

Rachid El-Azouzi

2014-09-01

Full Text Available Most of the existing works have been evaluated the performance of 802.11 multihop networks by considering the MAC layer or network layer separately. Knowing the nature of the multi-hop ad hoc networks, many factors in different layers are crucial for study the performance of MANET. In this paper we present a new analytic model for evaluating average end-to-end throughput in IEEE 802.11e multihop wireless networks. In particular, we investigate an intricate interaction among PHY, MAC and Network layers. For instance, we incorporate carrier sense threshold, transmission power, contention window size, retransmissions retry limit, multi rates, routing protocols and network topology together. We build a general cross-layered framework to represent multi-hop ad hoc networks with asymmetric topology and asymmetric traffic. We develop an analytical model to predict throughput of each connection as well as stability of forwarding queues at intermediate nodes in saturated networks. To the best of our knowledge, it seems that our work is the first wherein general topology and asymmetric parameters setup are considered in PHY/MAC/Network layers. Performance of such a system is also evaluated through simulation. We show that performance measures of the MAC layer are affected by the traffic intensity of flows to be forwarded. More precisely, attempt rate and collision probability are dependent on traffic flows, topology and routing.

Accelerated sampling by infinite swapping of path integral molecular dynamics with surface hopping

Science.gov (United States)

Lu, Jianfeng; Zhou, Zhennan

2018-02-01

To accelerate the thermal equilibrium sampling of multi-level quantum systems, the infinite swapping limit of a recently proposed multi-level ring polymer representation is investigated. In the infinite swapping limit, the ring polymer evolves according to an averaged Hamiltonian with respect to all possible surface index configurations of the ring polymer and thus connects the surface hopping approach to the mean-field path-integral molecular dynamics. A multiscale integrator for the infinite swapping limit is also proposed to enable efficient sampling based on the limiting dynamics. Numerical results demonstrate the huge improvement of sampling efficiency of the infinite swapping compared with the direct simulation of path-integral molecular dynamics with surface hopping.

Fast Conflict Resolution Based on Reinforcement Learning in Multi-agent System

Institute of Scientific and Technical Information of China (English)

PIAOSonghao; HONGBingrong; CHUHaitao

2004-01-01

In multi-agent system where each agen thas a different goal (even the team of agents has the same goal), agents must be able to resolve conflicts arising in the process of achieving their goal. Many researchers presented methods for conflict resolution, e.g., Reinforcement learning (RL), but the conventional RL requires a large computation cost because every agent must learn, at the same time the overlap of actions selected by each agent results in local conflict. Therefore in this paper, we propose a novel method to solve these problems. In order to deal with the conflict within the multi-agent system, the concept of potential field function based Action selection priority level (ASPL) is brought forward. In this method, all kinds of environment factor that may have influence on the priority are effectively computed with the potential field function. So the priority to access the local resource can be decided rapidly. By avoiding the complex coordination mechanism used in general multi-agent system, the conflict in multi-agent system is settled more efficiently. Our system consists of RL with ASPL module and generalized rules module. Using ASPL, RL module chooses a proper cooperative behavior, and generalized rule module can accelerate the learning process. By applying the proposed method to Robot Soccer, the learning process can be accelerated. The results of simulation and real experiments indicate the effectiveness of the method.

Multi-Role Project (MRP): A New Project-Based Learning Method for STEM

Science.gov (United States)

Warin, Bruno; Talbi, Omar; Kolski, Christophe; Hoogstoel, Frédéric

2016-01-01

This paper presents the "Multi-Role Project" method (MRP), a broadly applicable project-based learning method, and describes its implementation and evaluation in the context of a Science, Technology, Engineering, and Mathematics (STEM) course. The MRP method is designed around a meta-principle that considers the project learning activity…

An Online Q-learning Based Multi-Agent LFC for a Multi-Area Multi-Source Power System Including Distributed Energy Resources

Directory of Open Access Journals (Sweden)

H. Shayeghi

2017-12-01

Full Text Available This paper presents an online two-stage Q-learning based multi-agent (MA controller for load frequency control (LFC in an interconnected multi-area multi-source power system integrated with distributed energy resources (DERs. The proposed control strategy consists of two stages. The first stage is employed a PID controller which its parameters are designed using sine cosine optimization (SCO algorithm and are fixed. The second one is a reinforcement learning (RL based supplementary controller that has a flexible structure and improves the output of the first stage adaptively based on the system dynamical behavior. Due to the use of RL paradigm integrated with PID controller in this strategy, it is called RL-PID controller. The primary motivation for the integration of RL technique with PID controller is to make the existing local controllers in the industry compatible to reduce the control efforts and system costs. This novel control strategy combines the advantages of the PID controller with adaptive behavior of MA to achieve the desired level of robust performance under different kind of uncertainties caused by stochastically power generation of DERs, plant operational condition changes, and physical nonlinearities of the system. The suggested decentralized controller is composed of the autonomous intelligent agents, who learn the optimal control policy from interaction with the system. These agents update their knowledge about the system dynamics continuously to achieve a good frequency oscillation damping under various severe disturbances without any knowledge of them. It leads to an adaptive control structure to solve LFC problem in the multi-source power system with stochastic DERs. The results of RL-PID controller in comparison to the traditional PID and fuzzy-PID controllers is verified in a multi-area power system integrated with DERs through some performance indices.

Multi-Source Multi-Target Dictionary Learning for Prediction of Cognitive Decline.

Science.gov (United States)

Zhang, Jie; Li, Qingyang; Caselli, Richard J; Thompson, Paul M; Ye, Jieping; Wang, Yalin

2017-06-01

Alzheimer's Disease (AD) is the most common type of dementia. Identifying correct biomarkers may determine pre-symptomatic AD subjects and enable early intervention. Recently, Multi-task sparse feature learning has been successfully applied to many computer vision and biomedical informatics researches. It aims to improve the generalization performance by exploiting the shared features among different tasks. However, most of the existing algorithms are formulated as a supervised learning scheme. Its drawback is with either insufficient feature numbers or missing label information. To address these challenges, we formulate an unsupervised framework for multi-task sparse feature learning based on a novel dictionary learning algorithm. To solve the unsupervised learning problem, we propose a two-stage Multi-Source Multi-Target Dictionary Learning (MMDL) algorithm. In stage 1, we propose a multi-source dictionary learning method to utilize the common and individual sparse features in different time slots. In stage 2, supported by a rigorous theoretical analysis, we develop a multi-task learning method to solve the missing label problem. Empirical studies on an N = 3970 longitudinal brain image data set, which involves 2 sources and 5 targets, demonstrate the improved prediction accuracy and speed efficiency of MMDL in comparison with other state-of-the-art algorithms.

A Routing Strategy for Non-Cooperation Wireless Multi-Hop Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Dung T. Tran

2012-01-01

Full Text Available Choosing routes such that the network lifetime is maximized in a wireless network with limited energy resources is a major routing problem in wireless multi-hop ad hoc networks. In this paper, we study the problem where participants are rationally selfish and non-cooperative. By selfish we designate the users who are ready to tamper with their source-routing (senders could choose intermediate nodes in the routing paths or next hop selection strategies in order to increase the total number of packets transmitted, but do not try to harm or drop packets of the other nodes. The problem therefore amounts to a non-cooperative game. In the works [2,6,19,23], the authors show that the game admits Nash equilibria [1]. Along this line, we first show that if the cost function is linear, this game has pure-strategy equilibrium flow even though participants have different demands. However, finding a Nash equilibrium for a normal game is computationally hard [9]. In this work, inspired by mixed-strategy equilibrium, we propose a simple local routing algorithm called MIxed Path Routing protocol (MiPR. Using analysis and simulations, we show that MiPR drives the system to an equilibrium state where selfish participants do not have incentive to deviate. Moreover, MiPR significantly improves the network lifetime as compared to original routing protocols.

A study on a wheel-based stair-climbing robot with a hopping mechanism

Science.gov (United States)

Kikuchi, Koki; Sakaguchi, Keisuke; Sudo, Takayuki; Bushida, Naoki; Chiba, Yasuhiro; Asai, Yuji

2008-08-01

In this study, we propose a simple hopping mechanism using the vibration of a two-degree-of-freedom system for a wheel-based stair-climbing robot. The robot, consisting of two bodies connected by springs and a wire, hops by releasing energy stored in the springs and quickly travels using wheels mounted in its lower body. The trajectories of the bodies during hopping change in accordance with the design parameters, such as the reduced mass of the two bodies, the mass ratio between the upper and lower bodies, the spring constant, the control parameters such as the initial contraction of the spring and the wire tension. This property allows the robot to quickly and economically climb up and down stairs, leap over obstacles, and landing softly without complex control. In this paper, the characteristics of hopping motion for the design and control parameters are clarified by both numerical simulations and experiments. Furthermore, using the robot design based on the results the abilities to hop up and down a step, leap over a cable, and land softly are demonstrated.

Multi-viewpoint Smartphone AR-based Learning System for Solar Movement Observations

Directory of Open Access Journals (Sweden)

Ke Tian

2014-06-01

Full Text Available Understanding solar movement (e.g., solar diurnal motion is difficult for those are beginning to learn about astronomy. Previous research has revealed that observation-based learning can help make astronomical phenomena clearer to understand for such learners. In this research, Smartphone Augmented Reality (AR technology and 3D content were used to develop a multi-viewpoint Smartphone AR-based learning system (M-VSARLS for solar movement observations that can be used in the real-world environment. The goal of this research is to assess the usefulness of the system, usability of the AR function and 3D content, and the overall effect of the system on the learner’s motivation through task-based experiments with follow-up questionnaires. The results show that the M-VSARL system is effective in improving the observational skills and learning ability of learners, and in enhancing their motivation to learn about solar movement.

A Multi-Modal Digital Game-Based Learning Environment for Hospitalized Children with Chronic Illnesses.

Science.gov (United States)

Chin, Jui-Chih; Tsuei, Mengping

2014-01-01

The aim of this study was to explore the digital game-based learning for children with chronic illnesses in the hospital settings. The design-based research and qualitative methods were applied. Three eight-year-old children with leukemia participated in this study. In the first phase, the multi-user game-based learning system was developed and…

Active Multi-Field Learning for Spam Filtering

OpenAIRE

Wuying Liu; Lin Wang; Mianzhu Yi; Nan Xie

2015-01-01

Ubiquitous spam messages cause a serious waste of time and resources. This paper addresses the practical spam filtering problem, and proposes a universal approach to fight with various spam messages. The proposed active multi-field learning approach is based on: 1) It is cost-sensitive to obtain a label for a real-world spam filter, which suggests an active learning idea; and 2) Different messages often have a similar multi-field text structure, which suggests a multi-field learning idea. The...

Rectified-Linear-Unit-Based Deep Learning for Biomedical Multi-label Data.

Science.gov (United States)

Wang, Pu; Ge, Ruiquan; Xiao, Xuan; Cai, Yunpeng; Wang, Guoqing; Zhou, Fengfeng

2017-09-01

Disease diagnosis is one of the major data mining questions by the clinicians. The current diagnosis models usually have a strong assumption that one patient has only one disease, i.e. a single-label data mining problem. But the patients, especially when at the late stages, may have more than one disease and require a multi-label diagnosis. The multi-label data mining is much more difficult than a single-label one, and very few algorithms have been developed for this situation. Deep learning is a data mining algorithm with highly dense inner structure and has achieved many successful applications in the other areas. We propose a hypothesis that rectified-linear-unit-based deep learning algorithm may also be good at the clinical questions, by revising the last layer as a multi-label output. The proof-of-concept experimental data support the hypothesis, and the community may be interested in trying more applications.

An Adaptive Data Gathering Scheme for Multi-Hop Wireless Sensor Networks Based on Compressed Sensing and Network Coding.

Science.gov (United States)

Yin, Jun; Yang, Yuwang; Wang, Lei

2016-04-01

Joint design of compressed sensing (CS) and network coding (NC) has been demonstrated to provide a new data gathering paradigm for multi-hop wireless sensor networks (WSNs). By exploiting the correlation of the network sensed data, a variety of data gathering schemes based on NC and CS (Compressed Data Gathering--CDG) have been proposed. However, these schemes assume that the sparsity of the network sensed data is constant and the value of the sparsity is known before starting each data gathering epoch, thus they ignore the variation of the data observed by the WSNs which are deployed in practical circumstances. In this paper, we present a complete design of the feedback CDG scheme where the sink node adaptively queries those interested nodes to acquire an appropriate number of measurements. The adaptive measurement-formation procedure and its termination rules are proposed and analyzed in detail. Moreover, in order to minimize the number of overall transmissions in the formation procedure of each measurement, we have developed a NP-complete model (Maximum Leaf Nodes Minimum Steiner Nodes--MLMS) and realized a scalable greedy algorithm to solve the problem. Experimental results show that the proposed measurement-formation method outperforms previous schemes, and experiments on both datasets from ocean temperature and practical network deployment also prove the effectiveness of our proposed feedback CDG scheme.

Scheduling for dual-hop block-fading channels with two source-user pairs sharing one relay

KAUST Repository

Zafar, Ammar

2013-09-01

In this paper, we maximize the achievable rate region of a dual-hop network with two sources serving two users independently through a single shared relay. We formulate the problem as maximizing the sum of the weighted long term average throughputs of the two users under stability constraints on the long term throughputs of the source-user pairs. In order to solve the problem, we propose a joint user-and-hop scheduling scheme, which schedules the first or second hop opportunistically based on instantaneous channel state information, in order to exploit multiuser diversity and multihop diversity gains. Numerical results show that the proposed joint scheduling scheme enhances the achievable rate region as compared to a scheme that employs multi-user scheduling on the second-hop alone. Copyright © 2013 by the Institute of Electrical and Electronic Engineers, Inc.

A Hybrid DV-Hop Algorithm Using RSSI for Localization in Large-Scale Wireless Sensor Networks.

Science.gov (United States)

Cheikhrouhou, Omar; M Bhatti, Ghulam; Alroobaea, Roobaea

2018-05-08

With the increasing realization of the Internet-of-Things (IoT) and rapid proliferation of wireless sensor networks (WSN), estimating the location of wireless sensor nodes is emerging as an important issue. Traditional ranging based localization algorithms use triangulation for estimating the physical location of only those wireless nodes that are within one-hop distance from the anchor nodes. Multi-hop localization algorithms, on the other hand, aim at localizing the wireless nodes that can physically be residing at multiple hops away from anchor nodes. These latter algorithms have attracted a growing interest from research community due to the smaller number of required anchor nodes. One such algorithm, known as DV-Hop (Distance Vector Hop), has gained popularity due to its simplicity and lower cost. However, DV-Hop suffers from reduced accuracy due to the fact that it exploits only the network topology (i.e., number of hops to anchors) rather than the distances between pairs of nodes. In this paper, we propose an enhanced DV-Hop localization algorithm that also uses the RSSI values associated with links between one-hop neighbors. Moreover, we exploit already localized nodes by promoting them to become additional anchor nodes. Our simulations have shown that the proposed algorithm significantly outperforms the original DV-Hop localization algorithm and two of its recently published variants, namely RSSI Auxiliary Ranging and the Selective 3-Anchor DV-hop algorithm. More precisely, in some scenarios, the proposed algorithm improves the localization accuracy by almost 95%, 90% and 70% as compared to the basic DV-Hop, Selective 3-Anchor, and RSSI DV-Hop algorithms, respectively.

Security-Reliability Analysis of Noma-Based Multi-Hop Relay Networks in Presence of an Active Eavesdropper with Imperfect Eavesdropping CSI

Directory of Open Access Journals (Sweden)

Tran Tin Phu

2017-01-01

Full Text Available In this paper, we evaluate system performances of a multi-hop relay protocol with presence of an active eavesdropper. In the proposed protocol, a source attempts to transmit its data to a destination with assistance of multiple intermediate relays. From the eavesdropping Channel State Information (CSI estimated, the source and relays adjust their transmit power so that the eavesdropper cannot overhear the transmitted data. Moreover, to enhance throughput for the proposed system, Non-Orthogonal Multiple Access (NOMA technique with a simple power allocation is also proposed. We derive exact closed-form expressions of the Outage Probability (OP and throughput for the data transmission over Rayleigh fading channel. In addition, when the CSI estimation is imperfect, Intercept Probability (IP at the eavesdropper is derived. Finally, Monte Carlo simulations are presented to verify the theoretical derivations.

Co-Labeling for Multi-View Weakly Labeled Learning.

Science.gov (United States)

Xu, Xinxing; Li, Wen; Xu, Dong; Tsang, Ivor W

2016-06-01

It is often expensive and time consuming to collect labeled training samples in many real-world applications. To reduce human effort on annotating training samples, many machine learning techniques (e.g., semi-supervised learning (SSL), multi-instance learning (MIL), etc.) have been studied to exploit weakly labeled training samples. Meanwhile, when the training data is represented with multiple types of features, many multi-view learning methods have shown that classifiers trained on different views can help each other to better utilize the unlabeled training samples for the SSL task. In this paper, we study a new learning problem called multi-view weakly labeled learning, in which we aim to develop a unified approach to learn robust classifiers by effectively utilizing different types of weakly labeled multi-view data from a broad range of tasks including SSL, MIL and relative outlier detection (ROD). We propose an effective approach called co-labeling to solve the multi-view weakly labeled learning problem. Specifically, we model the learning problem on each view as a weakly labeled learning problem, which aims to learn an optimal classifier from a set of pseudo-label vectors generated by using the classifiers trained from other views. Unlike traditional co-training approaches using a single pseudo-label vector for training each classifier, our co-labeling approach explores different strategies to utilize the predictions from different views, biases and iterations for generating the pseudo-label vectors, making our approach more robust for real-world applications. Moreover, to further improve the weakly labeled learning on each view, we also exploit the inherent group structure in the pseudo-label vectors generated from different strategies, which leads to a new multi-layer multiple kernel learning problem. Promising results for text-based image retrieval on the NUS-WIDE dataset as well as news classification and text categorization on several real-world multi

Hip-Hop Is the Healer: Sense of Belonging and Diversity among Hip-Hop Collegians

Science.gov (United States)

Sulé, V. Thandi

2016-01-01

Sense of belonging is recognized as a factor contributing to persistence to graduation. Furthermore, interactional diversity is associated with learning and civic outcomes--touted higher education goals. Hip-hop culture, one of the most influential cultural creations of the mid-20th century, has succeeded in attracting devotees from diverse…

An SDN-Based Fingerprint Hopping Method to Prevent Fingerprinting Attacks

Directory of Open Access Journals (Sweden)

Zheng Zhao

2017-01-01

Full Text Available Fingerprinting attacks are one of the most severe threats to the security of networks. Fingerprinting attack aims to obtain the operating system information of target hosts to make preparations for future attacks. In this paper, a fingerprint hopping method (FPH is proposed based on software-defined networks to defend against fingerprinting attacks. FPH introduces the idea of moving target defense to show a hopping fingerprint toward the fingerprinting attackers. The interaction of the fingerprinting attack and its defense is modeled as a signal game, and the equilibriums of the game are analyzed to develop an optimal defense strategy. Experiments show that FPH can resist fingerprinting attacks effectively.

A Multi-Hop Clustering Mechanism for Scalable IoT Networks.

Science.gov (United States)

Sung, Yoonyoung; Lee, Sookyoung; Lee, Meejeong

2018-03-23

It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63-87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6-89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network.

Detecting mode hopping in single-longitudinal-mode fiber ring lasers based on an unbalanced fiber Michelson interferometer.

Science.gov (United States)

Ma, Mingxiang; Hu, Zhengliang; Xu, Pan; Wang, Wei; Hu, Yongming

2012-10-20

A method of detecting mode hopping for single-longitudinal-mode (SLM) fiber ring lasers has been proposed and experimentally demonstrated. The method that is based on an unbalanced Michelson interferometer (MI) utilizing phase generated carrier modulation instantly transforms mode-hopping dynamics into steep phase changes of the interferometer. Multiform mode hops in an SLM erbium-doped fiber ring laser with an 18.6 MHz mode spacing have been detected exactly in real-time domain and discussed in detail. Numerical results show that the MI-based method has a high testing sensitivity for identifying mode hopping, which will play a significant role in evaluating the output stability of SLM fiber lasers.

Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking.

Science.gov (United States)

Bae, Seung-Hwan; Yoon, Kuk-Jin

2018-03-01

Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively. We first define the tracklet confidence using the detectability and continuity of a tracklet, and decompose a multi-object tracking problem into small subproblems based on the tracklet confidence. We then solve the online multi-object tracking problem by associating tracklets and detections in different ways according to their confidence values. Based on this strategy, tracklets sequentially grow with online-provided detections, and fragmented tracklets are linked up with others without any iterative and expensive association steps. For more reliable association between tracklets and detections, we also propose a deep appearance learning method to learn a discriminative appearance model from large training datasets, since the conventional appearance learning methods do not provide rich representation that can distinguish multiple objects with large appearance variations. In addition, we combine online transfer learning for improving appearance discriminability by adapting the pre-trained deep model during online tracking. Experiments with challenging public datasets show distinct performance improvement over other state-of-the-arts batch and online tracking methods, and prove the effect and usefulness of the proposed methods for online multi-object tracking.

Power and delay optimisation in multi-hop wireless networks

KAUST Repository

Xia, Li

2014-02-05

In this paper, we study the optimisation problem of transmission power and delay in a multi-hop wireless network consisting of multiple nodes. The goal is to determine the optimal policy of transmission rates at various buffer and channel states in order to minimise the power consumption and the queueing delay of the whole network. With the assumptions of interference-free links and independently and identically distributed (i.i.d.) channel states, we formulate this problem using a semi-open Jackson network model for data transmission and a Markov model for channel states transition. We derive a difference equation of the system performance under any two different policies. The necessary and sufficient condition of optimal policy is obtained. We also prove that the system performance is monotonic with respect to (w.r.t.) the transmission rate and the optimal transmission rate can be either maximal or minimal. That is, the ‘bang-bang’ control is an optimal control. This optimality structure greatly reduces the problem complexity. Furthermore, we develop an iterative algorithm to find the optimal solution. Finally, we conduct the simulation experiments to demonstrate the effectiveness of our approach. We hope our work can shed some insights on solving this complicated optimisation problem.

Symbiosis-Based Alternative Learning Multi-Swarm Particle Swarm Optimization.

Science.gov (United States)

Niu, Ben; Huang, Huali; Tan, Lijing; Duan, Qiqi

2017-01-01

Inspired by the ideas from the mutual cooperation of symbiosis in natural ecosystem, this paper proposes a new variant of PSO, named Symbiosis-based Alternative Learning Multi-swarm Particle Swarm Optimization (SALMPSO). A learning probability to select one exemplar out of the center positions, the local best position, and the historical best position including the experience of internal and external multiple swarms, is used to keep the diversity of the population. Two different levels of social interaction within and between multiple swarms are proposed. In the search process, particles not only exchange social experience with others that are from their own sub-swarms, but also are influenced by the experience of particles from other fellow sub-swarms. According to the different exemplars and learning strategy, this model is instantiated as four variants of SALMPSO and a set of 15 test functions are conducted to compare with some variants of PSO including 10, 30 and 50 dimensions, respectively. Experimental results demonstrate that the alternative learning strategy in each SALMPSO version can exhibit better performance in terms of the convergence speed and optimal values on most multimodal functions in our simulation.

Multi-Agent Framework for Virtual Learning Spaces.

Science.gov (United States)

Sheremetov, Leonid; Nunez, Gustavo

1999-01-01

Discussion of computer-supported collaborative learning, distributed artificial intelligence, and intelligent tutoring systems focuses on the concept of agents, and describes a virtual learning environment that has a multi-agent system. Describes a model of interactions in collaborative learning and discusses agents for Web-based virtual…

Multi-scale learning based segmentation of glands in digital colonrectal pathology images.

Science.gov (United States)

Gao, Yi; Liu, William; Arjun, Shipra; Zhu, Liangjia; Ratner, Vadim; Kurc, Tahsin; Saltz, Joel; Tannenbaum, Allen

2016-02-01

Digital histopathological images provide detailed spatial information of the tissue at micrometer resolution. Among the available contents in the pathology images, meso-scale information, such as the gland morphology, texture, and distribution, are useful diagnostic features. In this work, focusing on the colon-rectal cancer tissue samples, we propose a multi-scale learning based segmentation scheme for the glands in the colon-rectal digital pathology slides. The algorithm learns the gland and non-gland textures from a set of training images in various scales through a sparse dictionary representation. After the learning step, the dictionaries are used collectively to perform the classification and segmentation for the new image.

Robust hopping based on virtual pendulum posture control

International Nuclear Information System (INIS)

Sharbafi, Maziar A; Ahmadabadi, Majid Nili; Yazdanpanah, Mohammad J; Maufroy, Christophe; Seyfarth, Andre

2013-01-01

A new control approach to achieve robust hopping against perturbations in the sagittal plane is presented in this paper. In perturbed hopping, vertical body alignment has a significant role for stability. Our approach is based on the virtual pendulum concept, recently proposed, based on experimental findings in human and animal locomotion. In this concept, the ground reaction forces are pointed to a virtual support point, named virtual pivot point (VPP), during motion. This concept is employed in designing the controller to balance the trunk during the stance phase. New strategies for leg angle and length adjustment besides the virtual pendulum posture control are proposed as a unified controller. This method is investigated by applying it on an extension of the spring loaded inverted pendulum (SLIP) model. Trunk, leg mass and damping are added to the SLIP model in order to make the model more realistic. The stability is analyzed by Poincaré map analysis. With fixed VPP position, stability, disturbance rejection and moderate robustness are achieved, but with a low convergence speed. To improve the performance and attain higher robustness, an event-based control of the VPP position is introduced, using feedback of the system states at apexes. Discrete linear quartic regulator is used to design the feedback controller. Considerable enhancements with respect to stability, convergence speed and robustness against perturbations and parameter changes are achieved. (paper)

SHOP: scaffold hopping by GRID-based similarity searches

DEFF Research Database (Denmark)

Bergmann, Rikke; Linusson, Anna; Zamora, Ismael

2007-01-01

A new GRID-based method for scaffold hopping (SHOP) is presented. In a fully automatic manner, scaffolds were identified in a database based on three types of 3D-descriptors. SHOP's ability to recover scaffolds was assessed and validated by searching a database spiked with fragments of known...... scaffolds were in the 31 top-ranked scaffolds. SHOP also identified new scaffolds with substantially different chemotypes from the queries. Docking analysis indicated that the new scaffolds would have similar binding modes to those of the respective query scaffolds observed in X-ray structures...

Hip-Hop, Social Justice, and Environmental Education: Toward a Critical Ecological Literacy

Science.gov (United States)

Cermak, Michael J.

2012-01-01

This essay describes an educational initiative that used environmentally themed (green) hip-hop to stimulate learning in an environmental science classroom. Students were then challenged to compose their own green hip-hop and their lyrics demonstrated skills that have thematic consistency around what is called a Critical Ecological Literacy (CEL).…

Problem Based Learning as a Cultural Tool for Health and Safety Learning in a Multi-national Company

DEFF Research Database (Denmark)

Adam, Henrik; Petersson, Eva

2013-01-01

The general background of this study is an interest in how cultural tools contribute to structuring learning activities. The specific interest is to explore how such tools co-determine employees’ problem solving actions in health, safety and environment (HSE) training activities in a multi...... learn to organise HSE actions in the context of using Problem Based Learning (PBL) applied as a cultural tool. More specifically, our interest is in how PBL promotes adult learning by drawing on learners’ experience and involving them in reflective and social processes in the given context......-national company context. Theoretically, the research takes its point of departure in a socio-cultural perspective on the role of cultural tools in learning, and in a complementary interest in the role of communicative framing of learning activities. In the research reported here, the focus is on how employees...

Fresh Faces, New Places: Moving beyond Teacher-Researcher Perspectives in Hip-Hop-Based Education Research

Science.gov (United States)

Irby, Decoteau J.; Hall, H. Bernard

2011-01-01

Grounded in critical and culturally relevant theory, hip-hop-based education (HHBE) research documents the use of hip-hop in educational settings. Despite the richness of the emerging field, overreliance on teacher-researcher perspectives leaves much to be desired. Little is known of the extent and ways HHBE is used by nonresearching K-12…

A multi-objective improved teaching-learning based optimization algorithm for unconstrained and constrained optimization problems

Directory of Open Access Journals (Sweden)

R. Venkata Rao

2014-01-01

Full Text Available The present work proposes a multi-objective improved teaching-learning based optimization (MO-ITLBO algorithm for unconstrained and constrained multi-objective function optimization. The MO-ITLBO algorithm is the improved version of basic teaching-learning based optimization (TLBO algorithm adapted for multi-objective problems. The basic TLBO algorithm is improved to enhance its exploration and exploitation capacities by introducing the concept of number of teachers, adaptive teaching factor, tutorial training and self-motivated learning. The MO-ITLBO algorithm uses a grid-based approach to adaptively assess the non-dominated solutions (i.e. Pareto front maintained in an external archive. The performance of the MO-ITLBO algorithm is assessed by implementing it on unconstrained and constrained test problems proposed for the Congress on Evolutionary Computation 2009 (CEC 2009 competition. The performance assessment is done by using the inverted generational distance (IGD measure. The IGD measures obtained by using the MO-ITLBO algorithm are compared with the IGD measures of the other state-of-the-art algorithms available in the literature. Finally, Lexicographic ordering is used to assess the overall performance of competitive algorithms. Results have shown that the proposed MO-ITLBO algorithm has obtained the 1st rank in the optimization of unconstrained test functions and the 3rd rank in the optimization of constrained test functions.

To overhear or not to overhear: a dilemma between network coding gain and energy consumption in multi-hop wireless networks

OpenAIRE

Javan, Nastooh Taheri; Sabaei, Masoud; Dehghan, Mehdi

2018-01-01

Any properly designed network coding technique can result in increased throughput and reliability of multi-hop wireless networks by taking advantage of the broadcast nature of wireless medium. In many inter-flow network coding schemes nodes are encouraged to overhear neighbours traffic in order to improve coding opportunities at the transmitter nodes. A study of these schemes reveal that some of the overheard packets are not useful for coding operation and thus this forced overhearing increas...

Sleep/wake scheduling scheme for minimizing end-to-end delay in multi-hop wireless sensor networks

Directory of Open Access Journals (Sweden)

Madani Sajjad

2011-01-01

Full Text Available Abstract We present a sleep/wake schedule protocol for minimizing end-to-end delay for event driven multi-hop wireless sensor networks. In contrast to generic sleep/wake scheduling schemes, our proposed algorithm performs scheduling that is dependent on traffic loads. Nodes adapt their sleep/wake schedule based on traffic loads in response to three important factors, (a the distance of the node from the sink node, (b the importance of the node's location from connectivity's perspective, and (c if the node is in the proximity where an event occurs. Using these heuristics, the proposed scheme reduces end-to-end delay and maximizes the throughput by minimizing the congestion at nodes having heavy traffic load. Simulations are carried out to evaluate the performance of the proposed protocol, by comparing its performance with S-MAC and Anycast protocols. Simulation results demonstrate that the proposed protocol has significantly reduced the end-to-end delay, as well as has improved the other QoS parameters, like average energy per packet, average delay, packet loss ratio, throughput, and coverage lifetime.

Ab initio calculation of diffusion barriers for Cu adatom hopping on Cu(1 0 0) surface and evolution of atomic configurations

Science.gov (United States)

Zhang, Wei; Gan, Jie; Li, Qian; Gao, Kun; Sun, Jian; Xu, Ning; Ying, Zhifeng; Wu, Jiada

2011-06-01

The self-diffusion dynamics of Cu adatoms on Cu(1 0 0) surface has been studied based on the calculation of the energy barriers for various hopping events using lattice-gas based approach and a modified model. To simplify the description of the interactions and the calculation of the energy barrier, a three-tier hierarchy of description of atomic configurations was conceived in which the active adatom and its nearest atoms were chosen to constitute basic configuration and taken as a whole to study many-body interactions of the atoms in various atomic configurations, whereas the impacts of the next nearest atoms on the diffusion of the active adatom were considered as multi-site interactions. Besides the simple hopping of single adatoms, the movements of dimers and trimers as the results of multiple hopping events have also been examined. Taking into account the hopping events of all adatoms, the stability of atomic configurations has been examined and the evolution of atomic configurations has also been analyzed.

Ab initio calculation of diffusion barriers for Cu adatom hopping on Cu(1 0 0) surface and evolution of atomic configurations

International Nuclear Information System (INIS)

Zhang Wei; Gan Jie; Li Qian; Gao Kun; Sun Jian; Xu Ning; Ying Zhifeng; Wu Jiada

2011-01-01

The self-diffusion dynamics of Cu adatoms on Cu(1 0 0) surface has been studied based on the calculation of the energy barriers for various hopping events using lattice-gas based approach and a modified model. To simplify the description of the interactions and the calculation of the energy barrier, a three-tier hierarchy of description of atomic configurations was conceived in which the active adatom and its nearest atoms were chosen to constitute basic configuration and taken as a whole to study many-body interactions of the atoms in various atomic configurations, whereas the impacts of the next nearest atoms on the diffusion of the active adatom were considered as multi-site interactions. Besides the simple hopping of single adatoms, the movements of dimers and trimers as the results of multiple hopping events have also been examined. Taking into account the hopping events of all adatoms, the stability of atomic configurations has been examined and the evolution of atomic configurations has also been analyzed.

Revolutionizing Environmental Education through Indigenous Hip Hop Culture

Science.gov (United States)

Gorlewski, Julie; Porfilio, Brad J.

2012-01-01

Based upon the life histories of six Indigenous hip hop artists of the Beat Nation artist collective, this essay captures how Indigenous hip hop has the potential to revolutionize environmental education. Hip hop provides Indigenous youth an emancipatory space to raise their opposition to neocolonial controls of Indigenous territories that…

A Contextualised Multi-Platform Framework to Support Blended Learning Scenarios in Learning Networks

NARCIS (Netherlands)

De Jong, Tim; Fuertes, Alba; Schmeits, Tally; Specht, Marcus; Koper, Rob

2008-01-01

De Jong, T., Fuertes, A., Schmeits, T., Specht, M., & Koper, R. (2009). A Contextualised Multi-Platform Framework to Support Blended Learning Scenarios in Learning Networks. In D. Goh (Ed.), Multiplatform E-Learning Systems and Technologies: Mobile Devices for Ubiquitous ICT-Based Education (pp.

Event-Triggered Fault Estimation for Stochastic Systems over Multi-Hop Relay Networks with Randomly Occurring Sensor Nonlinearities and Packet Dropouts.

Science.gov (United States)

Li, Yunji; Peng, Li

2018-02-28

Wireless sensors have many new applications where remote estimation is essential. Considering that a remote estimator is located far away from the process and the wireless transmission distance of sensor nodes is limited, sensor nodes always forward data packets to the remote estimator through a series of relays over a multi-hop link. In this paper, we consider a network with sensor nodes and relay nodes where the relay nodes can forward the estimated values to the remote estimator. An event-triggered remote estimator of state and fault with the corresponding data-forwarding scheme is investigated for stochastic systems subject to both randomly occurring nonlinearity and randomly occurring packet dropouts governed by Bernoulli-distributed sequences to achieve a trade-off between estimation accuracy and energy consumption. Recursive Riccati-like matrix equations are established to calculate the estimator gain to minimize an upper bound of the estimator error covariance. Subsequently, a sufficient condition and data-forwarding scheme are presented under which the error covariance is mean-square bounded in the multi-hop links with random packet dropouts. Furthermore, implementation issues of the theoretical results are discussed where a new data-forwarding communication protocol is designed. Finally, the effectiveness of the proposed algorithms and communication protocol are extensively evaluated using an experimental platform that was established for performance evaluation with a sensor and two relay nodes.

On using multiple routing metrics with destination sequenced distance vector protocol for MultiHop wireless ad hoc networks

Science.gov (United States)

Mehic, M.; Fazio, P.; Voznak, M.; Partila, P.; Komosny, D.; Tovarek, J.; Chmelikova, Z.

2016-05-01

A mobile ad hoc network is a collection of mobile nodes which communicate without a fixed backbone or centralized infrastructure. Due to the frequent mobility of nodes, routes connecting two distant nodes may change. Therefore, it is not possible to establish a priori fixed paths for message delivery through the network. Because of its importance, routing is the most studied problem in mobile ad hoc networks. In addition, if the Quality of Service (QoS) is demanded, one must guarantee the QoS not only over a single hop but over an entire wireless multi-hop path which may not be a trivial task. In turns, this requires the propagation of QoS information within the network. The key to the support of QoS reporting is QoS routing, which provides path QoS information at each source. To support QoS for real-time traffic one needs to know not only minimum delay on the path to the destination but also the bandwidth available on it. Therefore, throughput, end-to-end delay, and routing overhead are traditional performance metrics used to evaluate the performance of routing protocol. To obtain additional information about the link, most of quality-link metrics are based on calculation of the lost probabilities of links by broadcasting probe packets. In this paper, we address the problem of including multiple routing metrics in existing routing packets that are broadcasted through the network. We evaluate the efficiency of such approach with modified version of DSDV routing protocols in ns-3 simulator.

System optimization for peer-to-peer multi hop video broadcasting in wireless ad hoc networks

NARCIS (Netherlands)

Dedeoglu, V.; Atici, C.; Salman, F.S.; Sunay, M.O.

2008-01-01

We consider peer-to-peer video broadcasting using cooperation among peers in an ad hoc wireless network. As opposed to the traditional single hop broadcasting, multiple hops cause an increase in broadcast video quality while creating interference and increasing transmission delay. We develop

Digital case-based learning system in school.

Science.gov (United States)

Gu, Peipei; Guo, Jiayang

2017-01-01

With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework.

Digital case-based learning system in school.

Directory of Open Access Journals (Sweden)

Peipei Gu

Full Text Available With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework.

Landmark-based deep multi-instance learning for brain disease diagnosis.

Science.gov (United States)

Liu, Mingxia; Zhang, Jun; Adeli, Ehsan; Shen, Dinggang

2018-01-01

In conventional Magnetic Resonance (MR) image based methods, two stages are often involved to capture brain structural information for disease diagnosis, i.e., 1) manually partitioning each MR image into a number of regions-of-interest (ROIs), and 2) extracting pre-defined features from each ROI for diagnosis with a certain classifier. However, these pre-defined features often limit the performance of the diagnosis, due to challenges in 1) defining the ROIs and 2) extracting effective disease-related features. In this paper, we propose a landmark-based deep multi-instance learning (LDMIL) framework for brain disease diagnosis. Specifically, we first adopt a data-driven learning approach to discover disease-related anatomical landmarks in the brain MR images, along with their nearby image patches. Then, our LDMIL framework learns an end-to-end MR image classifier for capturing both the local structural information conveyed by image patches located by landmarks and the global structural information derived from all detected landmarks. We have evaluated our proposed framework on 1526 subjects from three public datasets (i.e., ADNI-1, ADNI-2, and MIRIAD), and the experimental results show that our framework can achieve superior performance over state-of-the-art approaches. Copyright © 2017 Elsevier B.V. All rights reserved.

Helicobacter pylori HopE and HopV porins present scarce expression among clinical isolates

Science.gov (United States)

Lienlaf, Maritza; Morales, Juan Pablo; Díaz, María Inés; Díaz, Rodrigo; Bruce, Elsa; Siegel, Freddy; León, Gloria; Harris, Paul R; Venegas, Alejandro

2010-01-01

AIM: To evaluate how widely Helicobacter pylori (H. pylori) HopE and HopV porins are expressed among Chilean isolates and how seroprevalent they are among infected patients in Chile. METHODS: H. pylori hopE and hopV genes derived from strain CHCTX-1 were cloned by polymerase chain reaction (PCR), sequenced and expressed in Escherichia coli AD494 (DE3). Gel-purified porins were used to prepare polyclonal antibodies. The presence of both genes was tested by PCR in a collection of H. pylori clinical isolates and their expression was detected in lysates by immunoblotting. Immune responses against HopE, HopV and other H. pylori antigens in sera from infected and non-infected patients were tested by Western blotting using these sera as first antibody on recombinant H. pylori antigens. RESULTS: PCR and Western blotting assays revealed that 60 and 82 out of 130 Chilean isolates carried hopE and hopV genes, respectively, but only 16 and 9, respectively, expressed these porins. IgG serum immunoreactivity evaluation of 69 H. pylori-infected patients revealed that HopE and HopV were infrequently recognized (8.7% and 10.1% respectively) compared to H. pylori VacA (68.1%) and CagA (59.5%) antigens. Similar values were detected for IgA serum immunoreactivity against HopE (11.6%) and HopV (10.5%) although lower values for VacA (42%) and CagA (17.4%) were obtained when compared to the IgG response. CONCLUSION: A scarce expression of HopE and HopV among Chilean isolates was found, in agreement with the infrequent seroconversion against these antigens when tested in infected Chilean patients. PMID:20082477

Hip-hop as a resource for understanding the urban context

Science.gov (United States)

Brown, Bryan

2010-06-01

This review explores Edmin's "Science education for the hip-hop generation" by documenting how he frames hip-hop as a means to access urban student culture. He argues that hip-hop is more than a mere music genre, but rather a culture that provides young people with ways of connecting to the world. Two primary ideas emerged as central to his work. First, he contends that students develop communal relationships and collective identities based on the common experiences expressed in hip-hop. Second, he identifies how the conscious recognition of institutional oppression serves a central feature in urban schools. Emdin's rich, and personal call for a greater understanding of hip-hop culture provides the text with an unmatched strength. He skillfully uses personal narratives from his own experience as well as quotes and references from hip-hop songs to make the nuances of hip hop transparent to science educators. Conversely, the limitation of this text is found in its unfulfilled promise to provide pragmatic examples of how to engage in a hip-hop based science education. Emdin's work is ultimately valuable as it extends our current knowledge about urban students and hip-hop in meaningful ways.

Examining Hip-Hop as Culturally Relevant Pedagogy

Science.gov (United States)

Kim, Jung; Pulido, Isaura

2015-01-01

Culturally relevant pedagogy is a framework that conceptualizes the process of student learning as contingent upon educators' deep understanding of students' cultural backgrounds to co-construct knowledge and develop academic skills. Concurrently, there are a growing number of studies that explore hip-hop as a culturally relevant curriculum for…

Bridging Theory and Practice: Using Hip-Hop Pedagogy as a Culturally Relevant Approach in the Urban Science Classroom

Science.gov (United States)

Adjapong, Edmund S.

2017-01-01

This dissertation explores the context of urban science education as it relates to the achievement and engagement of urban youth. This study provides a framework for Hip-Hop Pedagogy, an approach to teaching and learning anchored in the creative elements of Hip-Hop culture, in STEM as an innovative approach to teaching and learning demonstrates…

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification

Directory of Open Access Journals (Sweden)

Lu Bing

2017-01-01

Full Text Available We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL. After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM. Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification.

Science.gov (United States)

Bing, Lu; Wang, Wei

2017-01-01

We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL). After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM). Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Rethinking Pedagogy in Urban Spaces: Implementing Hip-Hop Pedagogy in the Urban Science Classroom

Science.gov (United States)

Adjapong, Edmund S.; Emdin, Christopher

2015-01-01

A significant amount of research regarding Hip-Hop Based Education (HHBE) fails to provide insight on how to incorporate elements of Hip-Hop into daily teaching practices; rather Hip-Hop based educators focus mainly on incorporating Hip-Hop culture into curricula. This study explores the benefits of using two specific Hip-Hop pedagogical practices…

Perceived bitterness character of beer in relation to hop variety and the impact of hop aroma.

Science.gov (United States)

Oladokun, Olayide; James, Sue; Cowley, Trevor; Dehrmann, Frieda; Smart, Katherine; Hort, Joanne; Cook, David

2017-09-01

The impact of hop variety and hop aroma on perceived beer bitterness intensity and character was investigated using analytical and sensory methods. Beers made from malt extract were hopped with 3 distinctive hop varieties (Hersbrucker, East Kent Goldings, Zeus) to achieve equi-bitter levels. A trained sensory panel determined the bitterness character profile of each singly-hopped beer using a novel lexicon. Results showed different bitterness character profiles for each beer, with hop aroma also found to change the hop variety-derived bitterness character profiles of the beer. Rank-rating evaluations further showed the significant effect of hop aroma on selected key bitterness character attributes, by increasing perceived harsh and lingering bitterness, astringency, and bitterness intensity via cross-modal flavour interactions. This study advances understanding of the complexity of beer bitterness perception by demonstrating that hop variety selection and hop aroma both impact significantly on the perceived intensity and character of this key sensory attribute. Copyright © 2017 Elsevier Ltd. All rights reserved.

Wheeled hopping robot

Science.gov (United States)

Fischer, Gary J [Albuquerque, NM

2010-08-17

The present invention provides robotic vehicles having wheeled and hopping mobilities that are capable of traversing (e.g. by hopping over) obstacles that are large in size relative to the robot and, are capable of operation in unpredictable terrain over long range. The present invention further provides combustion powered linear actuators, which can include latching mechanisms to facilitate pressurized fueling of the actuators, as can be used to provide wheeled vehicles with a hopping mobility.

Beer spoilage bacteria and hop resistance.

Science.gov (United States)

Sakamoto, Kanta; Konings, Wil N

2003-12-31

For brewing industry, beer spoilage bacteria have been problematic for centuries. They include some lactic acid bacteria such as Lactobacillus brevis, Lactobacillus lindneri and Pediococcus damnosus, and some Gram-negative bacteria such as Pectinatus cerevisiiphilus, Pectinatus frisingensis and Megasphaera cerevisiae. They can spoil beer by turbidity, acidity and the production of unfavorable smell such as diacetyl or hydrogen sulfide. For the microbiological control, many advanced biotechnological techniques such as immunoassay and polymerase chain reaction (PCR) have been applied in place of the conventional and time-consuming method of incubation on culture media. Subsequently, a method is needed to determine whether the detected bacterium is capable of growing in beer or not. In lactic acid bacteria, hop resistance is crucial for their ability to grow in beer. Hop compounds, mainly iso-alpha-acids in beer, have antibacterial activity against Gram-positive bacteria. They act as ionophores which dissipate the pH gradient across the cytoplasmic membrane and reduce the proton motive force (pmf). Consequently, the pmf-dependent nutrient uptake is hampered, resulting in cell death. The hop-resistance mechanisms in lactic acid bacteria have been investigated. HorA was found to excrete hop compounds in an ATP-dependent manner from the cell membrane to outer medium. Additionally, increased proton pumping by the membrane bound H(+)-ATPase contributes to hop resistance. To energize such ATP-dependent transporters hop-resistant cells contain larger ATP pools than hop-sensitive cells. Furthermore, a pmf-dependent hop transporter was recently presented. Understanding the hop-resistance mechanisms has enabled the development of rapid methods to discriminate beer spoilage strains from nonspoilers. The horA-PCR method has been applied for bacterial control in breweries. Also, a discrimination method was developed based on ATP pool measurement in lactobacillus cells. However

A Wheel-based Stair-climbing Robot with a Hopping Mechanism

OpenAIRE

Kikuchi, Koki; Bushida, Naoki; Sakaguchi, Keisuke; Chiba, Yasuhiro; Otsuka, Hiroshi; Saito, Yusuke; Hirano, Masamitsu; Kobayashi, Shunya

2010-01-01

We introduced a wheel-based stair-climbing robot with a hopping mechanism for stairclimbing. The robot, consisting of two body parts connected by springs, climbed stairs quickly, softly, and economically by using the vibration of a two-degrees-of-freedom system. In the future, we intend to shorten the required tread length by controlling the wire tension and minimizing the body length to realize a practical stair-climbing robot.

A Two-Stage Multi-Agent Based Assessment Approach to Enhance Students' Learning Motivation through Negotiated Skills Assessment

Science.gov (United States)

Chadli, Abdelhafid; Bendella, Fatima; Tranvouez, Erwan

2015-01-01

In this paper we present an Agent-based evaluation approach in a context of Multi-agent simulation learning systems. Our evaluation model is based on a two stage assessment approach: (1) a Distributed skill evaluation combining agents and fuzzy sets theory; and (2) a Negotiation based evaluation of students' performance during a training…

A fast-hopping 3-band CMOS frequency synthesizer for MB-OFDM UWB system

International Nuclear Information System (INIS)

Zheng Yongzheng; Xia Lingli; Li Weinan; Huang Yumei; Hong Zhiliang

2009-01-01

A fast-hopping 3-band (mode 1) multi-band orthogonal frequency division multiplexing ultra-wideband frequency synthesizer is presented. This synthesizer uses two phase-locked loops for generating steady frequencies and one quadrature single-sideband mixer for frequency shifting and quadrature frequency generation. The generated carriers can hop among 3432 MHz, 3960 MHz, and 4488 MHz. Implemented in a 0.13 μm CMOS process, this fully integrated synthesizer consumes 27 mA current from a 1.2 V supply. Measurement shows that the out-of-band spurious tones are below -50 dBc, while the in-band spurious tones are below -34 dBc. The measured hopping time is below 2 ns. The core die area is 1.0 x 1.8 mm 2 .

A fast-hopping 3-band CMOS frequency synthesizer for MB-OFDM UWB system

Energy Technology Data Exchange (ETDEWEB)

Zheng Yongzheng; Xia Lingli; Li Weinan; Huang Yumei; Hong Zhiliang, E-mail: yumeihuang@fudan.edu.c [State Key Laboratory of ASIC and System, Fudan University, Shanghai 201203 (China)

2009-09-15

A fast-hopping 3-band (mode 1) multi-band orthogonal frequency division multiplexing ultra-wideband frequency synthesizer is presented. This synthesizer uses two phase-locked loops for generating steady frequencies and one quadrature single-sideband mixer for frequency shifting and quadrature frequency generation. The generated carriers can hop among 3432 MHz, 3960 MHz, and 4488 MHz. Implemented in a 0.13 {mu}m CMOS process, this fully integrated synthesizer consumes 27 mA current from a 1.2 V supply. Measurement shows that the out-of-band spurious tones are below -50 dBc, while the in-band spurious tones are below -34 dBc. The measured hopping time is below 2 ns. The core die area is 1.0 x 1.8 mm{sup 2}.

Bridging Theory and Practice: Using Hip-Hop Pedagogy As A Culturally Relevant Approach In The Urban Science Classroom

Science.gov (United States)

Adjapong, Edmund S.

This dissertation explores the context of urban science education as it relates to the achievement and engagement of urban youth. This study provides a framework for Hip-Hop Pedagogy, an approach to teaching and learning anchored in the creative elements of Hip-Hop culture, in STEM as an innovative approach to teaching and learning demonstrates the effect that Hip-Hop Pedagogy, as a culturally relevant approach to teaching has on teaching and learning in an urban science classroom. This study establishes practical tools and approaches, which were formed from by theory and research that transcend the traditional monolithic approaches to teaching science. Participants in this study are middle school students who attend an urban school in one of the largest school systems in the country. This research showed that as result of utilizing Hip-Hop pedagogical practices, students reported that they developed a deeper understanding of science content, students were more likely to identify as scientists, and students were provided a space and opportunities to deconstruct traditional classroom spaces and structures.

Blind Compressed Sensing Parameter Estimation of Non-cooperative Frequency Hopping Signal

Directory of Open Access Journals (Sweden)

Chen Ying

2016-10-01

Full Text Available To overcome the disadvantages of a non-cooperative frequency hopping communication system, such as a high sampling rate and inadequate prior information, parameter estimation based on Blind Compressed Sensing (BCS is proposed. The signal is precisely reconstructed by the alternating iteration of sparse coding and basis updating, and the hopping frequencies are directly estimated based on the results. Compared with conventional compressive sensing, blind compressed sensing does not require prior information of the frequency hopping signals; hence, it offers an effective solution to the inadequate prior information problem. In the proposed method, the signal is first modeled and then reconstructed by Orthonormal Block Diagonal Blind Compressed Sensing (OBD-BCS, and the hopping frequencies and hop period are finally estimated. The simulation results suggest that the proposed method can reconstruct and estimate the parameters of noncooperative frequency hopping signals with a low signal-to-noise ratio.

Switching dynamics of multi-agent learning

NARCIS (Netherlands)

Vrancx, P.; Tuyls, K.P.; Westra, R.

2008-01-01

This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcement learning agents and replicator dynamics in stateless multi-agent games. More precisely, in this work we use a

Uncertainty Flow Facilitates Zero-Shot Multi-Label Learning in Affective Facial Analysis

Directory of Open Access Journals (Sweden)

Wenjun Bai

2018-02-01

Full Text Available Featured Application: The proposed Uncertainty Flow framework may benefit the facial analysis with its promised elevation in discriminability in multi-label affective classification tasks. Moreover, this framework also allows the efficient model training and between tasks knowledge transfer. The applications that rely heavily on continuous prediction on emotional valance, e.g., to monitor prisoners’ emotional stability in jail, can be directly benefited from our framework. Abstract: To lower the single-label dependency on affective facial analysis, it urges the fruition of multi-label affective learning. The impediment to practical implementation of existing multi-label algorithms pertains to scarcity of scalable multi-label training datasets. To resolve this, an inductive transfer learning based framework, i.e.,Uncertainty Flow, is put forward in this research to allow knowledge transfer from a single labelled emotion recognition task to a multi-label affective recognition task. I.e., the model uncertainty—which can be quantified in Uncertainty Flow—is distilled from a single-label learning task. The distilled model uncertainty ensures the later efficient zero-shot multi-label affective learning. On the theoretical perspective, within our proposed Uncertainty Flow framework, the feasibility of applying weakly informative priors, e.g., uniform and Cauchy prior, is fully explored in this research. More importantly, based on the derived weight uncertainty, three sets of prediction related uncertainty indexes, i.e., soft-max uncertainty, pure uncertainty and uncertainty plus are proposed to produce reliable and accurate multi-label predictions. Validated on our manual annotated evaluation dataset, i.e., the multi-label annotated FER2013, our proposed Uncertainty Flow in multi-label facial expression analysis exhibited superiority to conventional multi-label learning algorithms and multi-label compatible neural networks. The success of our

Integrating model checking with HiP-HOPS in model-based safety analysis

International Nuclear Information System (INIS)

Sharvia, Septavera; Papadopoulos, Yiannis

2015-01-01

The ability to perform an effective and robust safety analysis on the design of modern safety–critical systems is crucial. Model-based safety analysis (MBSA) has been introduced in recent years to support the assessment of complex system design by focusing on the system model as the central artefact, and by automating the synthesis and analysis of failure-extended models. Model checking and failure logic synthesis and analysis (FLSA) are two prominent MBSA paradigms. Extensive research has placed emphasis on the development of these techniques, but discussion on their integration remains limited. In this paper, we propose a technique in which model checking and Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) – an advanced FLSA technique – can be applied synergistically with benefit for the MBSA process. The application of the technique is illustrated through an example of a brake-by-wire system. - Highlights: • We propose technique to integrate HiP-HOPS and model checking. • State machines can be systematically constructed from HiP-HOPS. • The strengths of different MBSA techniques are combined. • Demonstrated through modeling and analysis of brake-by-wire system. • Root cause analysis is automated and system dynamic behaviors analyzed and verified

Mode-hopping mechanism generating colored noise in a magnetic tunnel junction based spin torque oscillator

International Nuclear Information System (INIS)

Sharma, Raghav; Dürrenfeld, P.; Iacocca, E.; Heinonen, O. G.; Åkerman, J.; Muduli, P. K.

2014-01-01

The frequency noise spectrum of a magnetic tunnel junction based spin torque oscillator is examined where multiple modes and mode-hopping events are observed. The frequency noise spectrum is found to consist of both white noise and 1/f frequency noise. We find a systematic and similar dependence of both white noise and 1/f frequency noise on bias current and the relative angle between the reference and free layers, which changes the effective damping and hence the mode-hopping behavior in this system. The frequency at which the 1/f frequency noise changes to white noise increases as the free layer is aligned away from the anti-parallel orientation w.r.t the reference layer. These results indicate that the origin of 1/f frequency noise is related to mode-hopping, which produces both white noise as well as 1/f frequency noise similar to the case of ring lasers.

A diagram retrieval method with multi-label learning

Science.gov (United States)

Fu, Songping; Lu, Xiaoqing; Liu, Lu; Qu, Jingwei; Tang, Zhi

2015-01-01

In recent years, the retrieval of plane geometry figures (PGFs) has attracted increasing attention in the fields of mathematics education and computer science. However, the high cost of matching complex PGF features leads to the low efficiency of most retrieval systems. This paper proposes an indirect classification method based on multi-label learning, which improves retrieval efficiency by reducing the scope of compare operation from the whole database to small candidate groups. Label correlations among PGFs are taken into account for the multi-label classification task. The primitive feature selection for multi-label learning and the feature description of visual geometric elements are conducted individually to match similar PGFs. The experiment results show the competitive performance of the proposed method compared with existing PGF retrieval methods in terms of both time consumption and retrieval quality.

Multi-agent machine learning a reinforcement approach

CERN Document Server

Schwartz, H M

2014-01-01

The book begins with a chapter on traditional methods of supervised learning, covering recursive least squares learning, mean square error methods, and stochastic approximation. Chapter 2 covers single agent reinforcement learning. Topics include learning value functions, Markov games, and TD learning with eligibility traces. Chapter 3 discusses two player games including two player matrix games with both pure and mixed strategies. Numerous algorithms and examples are presented. Chapter 4 covers learning in multi-player games, stochastic games, and Markov games, focusing on learning multi-pla

An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis

Science.gov (United States)

Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu

2018-05-01

The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.

Extreme Kinematics in Selected Hip Hop Dance Sequences.

Science.gov (United States)

Bronner, Shaw; Ojofeitimi, Sheyi; Woo, Helen

2015-09-01

Hip hop dance has many styles including breakdance (breaking), house, popping and locking, funk, streetdance, krumping, Memphis jookin', and voguing. These movements combine the complexity of dance choreography with the challenges of gymnastics and acrobatic movements. Despite high injury rates in hip hop dance, particularly in breakdance, to date there are no published biomechanical studies in this population. The purpose of this study was to compare representative hip hop steps found in breakdance (toprock and breaking) and house and provide descriptive statistics of the angular displacements that occurred in these sequences. Six expert female hip hop dancers performed three choreographed dance sequences, top rock, breaking, and house, to standardized music-based tempos. Hip, knee, and ankle kinematics were collected during sequences that were 18 to 30 sec long. Hip, knee, and ankle three-dimensional peak joint angles were compared in repeated measures ANOVAs with post hoc tests where appropriate (pHip hop maximal joint angles exceeded reported activities of daily living and high injury sports such as gymnastics. Hip hop dancers work at weight-bearing joint end ranges where muscles are at a functional disadvantage. These results may explain why lower extremity injury rates are high in this population.

Neighbor discovery in multi-hop wireless networks: evaluation and dimensioning with interferences considerations

Directory of Open Access Journals (Sweden)

Elyes Ben Hamida

2008-04-01

Full Text Available In this paper, we study the impact of collisions and interferences on a neighbor discovery process in the context of multi-hop wireless networks. We consider three models in which interferences and collisions are handled in very different ways. From an ideal channel where simultaneous transmissions do not interfere, we derive an alternate channel where simultaneous transmissions are considered two-by-two under the form of collisions, to finally reach a more realistic channel where simultaneous transmissions are handled under the form of shot-noise interferences. In these models, we analytically compute the link probability success between two neighbors as well as the expected number of nodes that correctly receive a Hello packet. Using this analysis, we show that if the neighbor discovery process is asymptotically equivalent in the three models, it offers very different behaviors locally in time. In particular, the scalability of the process is not the same depending on the way interferences are handled. Finally, we apply our results to the dimensioning of a Hello protocol parameters. We propose a method to adapt the protocol parameters to meet application constraints on the neighbor discovery process and to minimize the protocol energy consumption.

Multi-task Vector Field Learning.

Science.gov (United States)

Lin, Binbin; Yang, Sen; Zhang, Chiyuan; Ye, Jieping; He, Xiaofei

2012-01-01

Multi-task learning (MTL) aims to improve generalization performance by learning multiple related tasks simultaneously and identifying the shared information among tasks. Most of existing MTL methods focus on learning linear models under the supervised setting. We propose a novel semi-supervised and nonlinear approach for MTL using vector fields. A vector field is a smooth mapping from the manifold to the tangent spaces which can be viewed as a directional derivative of functions on the manifold. We argue that vector fields provide a natural way to exploit the geometric structure of data as well as the shared differential structure of tasks, both of which are crucial for semi-supervised multi-task learning. In this paper, we develop multi-task vector field learning (MTVFL) which learns the predictor functions and the vector fields simultaneously. MTVFL has the following key properties. (1) The vector fields MTVFL learns are close to the gradient fields of the predictor functions. (2) Within each task, the vector field is required to be as parallel as possible which is expected to span a low dimensional subspace. (3) The vector fields from all tasks share a low dimensional subspace. We formalize our idea in a regularization framework and also provide a convex relaxation method to solve the original non-convex problem. The experimental results on synthetic and real data demonstrate the effectiveness of our proposed approach.

Probabilistic Routing Based on Two-Hop Information in Delay/Disruption Tolerant Networks

Directory of Open Access Journals (Sweden)

Xu Wang

2015-01-01

Full Text Available We investigate an opportunistic routing protocol in delay/disruption tolerant networks (DTNs where the end-to-end path between source and destination nodes may not exist for most of the time. Probabilistic routing protocol using history of encounters and transitivity (PRoPHET is an efficient history-based routing protocol specifically proposed for DTNs, which only utilizes the delivery predictability of one-hop neighbors to make a decision for message forwarding. In order to further improve the message delivery rate and to reduce the average overhead of PRoPHET, in this paper we propose an improved probabilistic routing algorithm (IPRA, where the history information of contacts for the immediate encounter and two-hop neighbors has been jointly used to make an informed decision for message forwarding. Based on the Opportunistic Networking Environment (ONE simulator, the performance of IPRA has been evaluated via extensive simulations. The results show that IPRA can significantly improve the average delivery rate while achieving a better or comparable performance with respect to average overhead, average delay, and total energy consumption compared with the existing algorithms.

A Review of Hip Hop-Based Interventions for Health Literacy, Health Behaviors, and Mental Health.

Science.gov (United States)

Robinson, Cendrine; Seaman, Elizabeth L; Montgomery, LaTrice; Winfrey, Adia

2017-07-01

African-American children and adolescents experience an undue burden of disease for many health outcomes compared to their White peers. More research needs to be completed for this priority population to improve their health outcomes and ameliorate health disparities. Integrating hip hop music or hip hop dance into interventions may help engage African-American youth in health interventions and improve their health outcomes. We conducted a review of the literature to characterize hip hop interventions and determine their potential to improve health. We searched Web of Science, Scopus, PsycINFO, and EMBASE to identify studies that assessed hip hop interventions. To be included, studies had to (1) be focused on a psychosocial or physical health intervention that included hip hop and (2) present quantitative data assessing intervention outcomes. Twenty-three articles were identified as meeting all inclusion criteria and were coded by two reviewers. Articles were assessed with regards to sample characteristics, study design, analysis, intervention components, and results. Hip hop interventions have been developed to improve health literacy, health behavior, and mental health. The interventions were primarily targeted to African-American and Latino children and adolescents. Many of the health literacy and mental health studies used non-experimental study designs. Among the 12 (of 14) health behavior studies that used experimental designs, the association between hip hop interventions and positive health outcomes was inconsistent. The number of experimental hip hop intervention studies is limited. Future research is required to determine if hip hop interventions can promote health.

Charge transport properties of DNA aperiodic molecule: The role of interbase hopping in Watson-Crick base pair

Science.gov (United States)

Sinurat, E. N.; Yudiarsah, E.

2017-07-01

The charge transport properties of DNA aperiodic molecule has been studied by considering various interbase hopping parameter on Watson-Crick base pair. 32 base pairs long double-stranded DNA aperiodic model with sequence GCTAGTACGTGACGTAGCTAGGATATGCCTGA on one chain and its complement on the other chain is used. Transfer matrix method has been used to calculate transmission probabilities, for determining I-V characteristic using Landauer Büttiker formula. DNA molecule is modeled using tight binding hamiltonian combined with the theory of Slater-Koster. The result show, the increment of Watson-Crick hopping value leads to the transmission probabilities and current of DNA aperiodic molecule increases.

Time and Energy Efficient Relay Transmission for Multi-Hop Wireless Sensor Networks.

Science.gov (United States)

Kim, Jin-Woo; Barrado, José Ramón Ramos; Jeon, Dong-Keun

2016-06-27

The IEEE 802.15.4 standard is widely recognized as one of the most successful enabling technologies for short range low rate wireless communications and it is used in IoT applications. It covers all the details related to the MAC and PHY layers of the IoT protocol stack. Due to the nature of IoT, the wireless sensor networks are autonomously self-organized networks without infrastructure support. One of the issues in IoT is the network scalability. To address this issue, it is necessary to support the multi-hop topology. The IEEE 802.15.4 network can support a star, peer-to-peer, or cluster-tree topology. One of the IEEE 802.15.4 topologies suited for the high predictability of performance guarantees and energy efficient behavior is a cluster-tree topology where sensor nodes can switch off their transceivers and go into a sleep state to save energy. However, the IEEE 802.15.4 cluster-tree topology may not be able to provide sufficient bandwidth for the increased traffic load and the additional information may not be delivered successfully. The common drawback of the existing approaches is that they do not address the poor bandwidth utilization problem in IEEE 802.15.4 cluster-tree networks, so it is difficult to increase the network performance. Therefore, to solve this problem in this paper we study a relay transmission protocol based on the standard protocol in the IEEE 802.15.4 MAC. In the proposed scheme, the coordinators can relay data frames to their parent devices or their children devices without contention and can provide bandwidth for the increased traffic load or the number of devices. We also evaluate the performance of the proposed scheme through simulation. The simulation results demonstrate that the proposed scheme can improve the reliability, the end-to-end delay, and the energy consumption.

HapHop-Physio: a computer game to support cognitive therapies in children.

Science.gov (United States)

Rico-Olarte, Carolina; López, Diego M; Narváez, Santiago; Farinango, Charic D; Pharow, Peter S

2017-01-01

Care and support of children with physical or mental disabilities are accompanied with serious concerns for parents, families, healthcare institutions, schools, and their communities. Recent studies and technological innovations have demonstrated the feasibility of providing therapy and rehabilitation services to children supported by computer games. The aim of this paper is to present HapHop-Physio, an innovative computer game that combines exercise with fun and learning, developed to support cognitive therapies in children. Conventional software engineering methods such as the Scrum methodology, a functionality test and a related usability test, were part of the comprehensive methodology adapted to develop HapHop-Physio. The game supports visual and auditory attention therapies, as well as visual and auditory memory activities. The game was developed by a multidisciplinary team, which was based on the Hopscotch ® platform provided by Fraunhofer Institute for Digital Media Technology IDMT Institute in Germany, and designed in collaboration with a rehabilitation clinic in Colombia. HapHop-Physio was tested and evaluated to probe its functionality and user satisfaction. The results show the development of an easy-to-use and funny game by a multidisciplinary team using state-of-the-art videogame technologies and software methodologies. Children testing the game concluded that they would like to play again while undergoing rehabilitation therapies.

A fast learning method for large scale and multi-class samples of SVM

Science.gov (United States)

Fan, Yu; Guo, Huiming

2017-06-01

A multi-class classification SVM(Support Vector Machine) fast learning method based on binary tree is presented to solve its low learning efficiency when SVM processing large scale multi-class samples. This paper adopts bottom-up method to set up binary tree hierarchy structure, according to achieved hierarchy structure, sub-classifier learns from corresponding samples of each node. During the learning, several class clusters are generated after the first clustering of the training samples. Firstly, central points are extracted from those class clusters which just have one type of samples. For those which have two types of samples, cluster numbers of their positive and negative samples are set respectively according to their mixture degree, secondary clustering undertaken afterwards, after which, central points are extracted from achieved sub-class clusters. By learning from the reduced samples formed by the integration of extracted central points above, sub-classifiers are obtained. Simulation experiment shows that, this fast learning method, which is based on multi-level clustering, can guarantee higher classification accuracy, greatly reduce sample numbers and effectively improve learning efficiency.

Mic Power? Connections and the hip hop nation in Kampala, Uganda

DEFF Research Database (Denmark)

Schneidermann, Nanna

2014-01-01

Hip hop culture has been celebrated in the media and scholarship as a universal youth language, part of a global hip hop nation, and a type of counter-public. This article examines the everyday meanings and practices of hip hop among hip hop activists in Kampala, Uganda, specifically within...... the Batuuze rap group. Rather than portraying hip hop as a counter-public of the disempowered, I argue that the Batuuze engagement is based on what I call moral economy that enables the negotiation of connections in social and cultural networks towards what is considered a good life. Here, the hip hop nation...... is less of an alternative public sphere and more a way of articulating and contextualizing the world in a specific locality, which produces connections and opportunities in the young rappers’ lives....

Multi-population genomic prediction using a multi-task Bayesian learning model.

Science.gov (United States)

Chen, Liuhong; Li, Changxi; Miller, Stephen; Schenkel, Flavio

2014-05-03

Genomic prediction in multiple populations can be viewed as a multi-task learning problem where tasks are to derive prediction equations for each population and multi-task learning property can be improved by sharing information across populations. The goal of this study was to develop a multi-task Bayesian learning model for multi-population genomic prediction with a strategy to effectively share information across populations. Simulation studies and real data from Holstein and Ayrshire dairy breeds with phenotypes on five milk production traits were used to evaluate the proposed multi-task Bayesian learning model and compare with a single-task model and a simple data pooling method. A multi-task Bayesian learning model was proposed for multi-population genomic prediction. Information was shared across populations through a common set of latent indicator variables while SNP effects were allowed to vary in different populations. Both simulation studies and real data analysis showed the effectiveness of the multi-task model in improving genomic prediction accuracy for the smaller Ayshire breed. Simulation studies suggested that the multi-task model was most effective when the number of QTL was small (n = 20), with an increase of accuracy by up to 0.09 when QTL effects were lowly correlated between two populations (ρ = 0.2), and up to 0.16 when QTL effects were highly correlated (ρ = 0.8). When QTL genotypes were included for training and validation, the improvements were 0.16 and 0.22, respectively, for scenarios of the low and high correlation of QTL effects between two populations. When the number of QTL was large (n = 200), improvement was small with a maximum of 0.02 when QTL genotypes were not included for genomic prediction. Reduction in accuracy was observed for the simple pooling method when the number of QTL was small and correlation of QTL effects between the two populations was low. For the real data, the multi-task model achieved an

Hip-Hop High School: A Study of the Attitudes, Beliefs and Perceptions of Suburban High School Faculty towards Representation of the Hip-Hop Culture

Science.gov (United States)

Rowland, Ronald K.

2011-01-01

Research historically has demonstrated that a generational disconnect between the popular cultures from which students and teachers define normative behavior can impact classroom management and student learning. The purpose of this study was to examine attitudes, beliefs and perceptions of high school faculty toward the hip-hop culture and its…

Featherless Dinosaurs and the Hip-Hop Simulacrum: Reconsidering Hip-Hop's Appropriateness for the Music Classroom

Science.gov (United States)

Kruse, Adam J.

2016-01-01

This article offers considerations for music teachers interested in including hip-hop music in their classrooms but who might feel concerned with or overwhelmed by issues of appropriateness. Two concerns related to hip-hop music are examined: language and negative social themes. Commercial interests in hip-hop music have created a simulacrum (or…

Hopping transport in solids

CERN Document Server

Pollak, M

1991-01-01

The hopping process, which differs substantially from conventional transport processes in crystals, is the central process in the transport phenomena discussed in this book. Throughout the book the term ``hopping'' is defined as the inelastic tunneling transfer of an electron between two localized electronic states centered at different locations. Such processes do not occur in conventional electronic transport in solids, since localized states are not compatible with the translational symmetry of crystals.The rapid growth of interest in hopping transport has followed in the footsteps of the

SDN-Based Double Hopping Communication against Sniffer Attack

Directory of Open Access Journals (Sweden)

Zheng Zhao

2016-01-01

Full Text Available Sniffer attack has been a severe threat to network communication security. Traditional network usually uses static network configuration, which provides convenience to sniffer attack. In this paper, an SDN-based double hopping communication (DHC approach is proposed to solve this problem. In DHC, ends in communication packets as well as the routing paths are changed dynamically. Therefore, the traffic will be distributed to multiple flows and transmitted along different paths. Moreover, the data from multiple users will be mixed, bringing difficulty for attackers in obtaining and recovering the communication data, so that sniffer attack will be prevented effectively. It is concluded that DHC is able to increase the overhead of sniffer attack, as well as the difficulty of communication data recovery.

Multi-issue Agent Negotiation Based on Fairness

Science.gov (United States)

Zuo, Baohe; Zheng, Sue; Wu, Hong

Agent-based e-commerce service has become a hotspot now. How to make the agent negotiation process quickly and high-efficiently is the main research direction of this area. In the multi-issue model, MAUT(Multi-attribute Utility Theory) or its derived theory usually consider little about the fairness of both negotiators. This work presents a general model of agent negotiation which considered the satisfaction of both negotiators via autonomous learning. The model can evaluate offers from the opponent agent based on the satisfaction degree, learn online to get the opponent's knowledge from interactive instances of history and negotiation of this time, make concessions dynamically based on fair object. Through building the optimal negotiation model, the bilateral negotiation achieved a higher efficiency and fairer deal.

Supercritical fluid extraction of hops

Directory of Open Access Journals (Sweden)

ZORAN ZEKOVIC

2007-01-01

Full Text Available Five cultivars of hop were extracted by the method of supercritical fluid extraction using carbon dioxide (SFE–CO2 as extractant. The extraction (50 g of hop sample using a CO2 flow rate of 97.725 L/h was done in the two steps: 1. extraction at 150 bar and 40°C for 2.5 h (sample of series A was obtained and, after that, the same sample of hop was extracted in the second step: 2. extraction at 300 bar and 40 °C for 2.5 h (sample of series B was obtained. The Magnum cultivar was chosen for the investigation of the extraction kinetics. For the qualitative and quantitative analysis of the obtained hop extracts, the GC-MS method was used. Two of four themost common compounds of hop aroma (a-humulene and b-caryophyllene were detected in samples of series A. In addition, isomerized a-acids and a high content of b-acids were detected. The a-acids content in the samples of series B was the highest in the extract of the Magnum cultivar (it is a bitter variety of hop. The low contents of a-acids in all the other hop samples resulted in extracts with low a-acids content, i.e., that contents were under the prescribed a-acids content.

Design and Dynamics Analysis of a Bio-Inspired Intermittent Hopping Robot for Planetary Surface Exploration

Directory of Open Access Journals (Sweden)

Long Bai

2012-10-01

Full Text Available A small, bio-inspired and minimally actuated intermittent hopping robot for planetary surface exploration is proposed in this paper. The robot uses a combined-geared six-bar linkage/spring mechanism, which has a possible rich trajectory and metamorphic characteristics and, due to this, the robot is able to recharge, lock/release and jump by using just a micro-power motor as the actuator. Since the robotic system has a closed-chain structure and employs underactuated redundant motion, the constrained multi-body dynamics are derived with time-varying driving parameters and ground unilateral constraint both taken into consideration. In addition, the established dynamics equations, mixed of higher order differential and algebraic expressions, are solved by the immediate integration algorithm. A prototype is implemented and experiments are carried out. The results show that the robot, using a micro-power motor as the actuator and solar cells as the power supply, can achieve a biomimetic multi-body hopping stance and a nonlinearly increasing driving force. Typically, the robot can jump a horizontal distance of about 1 m and a vertical height of about 0.3 m, with its trunk and foot moving stably during takeoff. In addition, the computational and experimental results are consistent as regards the hopping performance of the robot, which suggests that the proposed dynamics model and its solution have general applicability to motion prediction and the performance analysis of intermittent hopping robots.

Development of aromatic hop compounds and bitterness in beer during room temperature- and cold storage based on three different hopping methods

OpenAIRE

Torgals, Ann Elisabeth

2015-01-01

The main objective of this study was to determine whether storage temperature or hopping method had influence on the aroma and bitterness in beer. The focus was set on the aroma that comes from hops, and not from yeast. The secondary objective to this study was to explore the development of the alcohol, CO2 and bitterness in the beer after priming and bottling. The thesis’ main perspective is that of home brewers, and to some extent that of microbreweries. Beer was brewed with 100 % pilsn...

Family-based hip-hop to health: outcome results.

Science.gov (United States)

Fitzgibbon, Marian L; Stolley, Melinda R; Schiffer, Linda; Kong, Angela; Braunschweig, Carol L; Gomez-Perez, Sandra L; Odoms-Young, Angela; Van Horn, Linda; Christoffel, Katherine Kaufer; Dyer, Alan R

2013-02-01

This pilot study tested the feasibility of Family-Based Hip-Hop to Health, a school-based obesity prevention intervention for 3-5-year-old Latino children and their parents, and estimated its effectiveness in producing smaller average changes in BMI at 1-year follow-up. Four Head Start preschools administered through the Chicago Public Schools were randomly assigned to receive a Family-Based Intervention (FBI) or a General Health Intervention (GHI). Parents signed consent forms for 147 of the 157 children enrolled. Both the school-based and family-based components of the intervention were feasible, but attendance for the parent intervention sessions was low. Contrary to expectations, a downtrend in BMI Z-score was observed in both the intervention and control groups. While the data reflect a downward trend in obesity among these young Hispanic children, obesity rates remained higher at 1-year follow-up (15%) than those reported by the National Health and Nutrition Examination Survey (2009-2010) for 2-5-year-old children (12.1%). Developing evidence-based strategies for obesity prevention among Hispanic families remains a challenge. Copyright © 2012 The Obesity Society.

OWL model of multi-agent Smart-system of distance learning for people with vision disabilities

Directory of Open Access Journals (Sweden)

Galina A. Samigulina

2017-01-01

Full Text Available The aim of the study is to develop an ontological model of multiagent smart-system of distance learning for visually impaired people based on Java Agent Development Framework for obtaining high-quality engineering education in laboratories of join use on modern equipment.Materials and methods of research. In developing multi-agent smart-system of distance learning, using various agents based on cognitive, ontological, statistical and intellectual methods is important. It is more convenient to implement this task in the form of software using multi-agent approach and Java Agent Development Framework. The main advantages of the platform are stability of operation, clear interface, simplicity of creating agents and extensive user database. In multi-agent systems, the solution is obtained automatically as result of interaction of many independent, purposeful agents. Each agent can perform certain tasks and pursue specified goals. Intellectual multi-agent systems and practical applications in distance learning based on them are considered.Results. The structural diagram of functioning of smart system distance learning for visually impaired people using various agents based on the system approach and the multi-agent platform Java Agent Development Framework is developed. The complex approach of distance learning of visually impaired people for obtaining highquality engineering education in laboratories of joint use on modern equipment is offered.The ontological model of multi-agent smart-system with a detailed description of the functions of following agents is created: personal, manager, ontological, cognitive, statistical, intellectual, shared laboratory agent, health agent, assistant to the agent and state agent. These agents execute their individual functions and provide a quality environment for learning.Conclusion. Thus, the proposed smart-system of distance learning for visually impaired people can significantly improve effectiveness and

Instance annotation for multi-instance multi-label learning

Science.gov (United States)

F. Briggs; X.Z. Fern; R. Raich; Q. Lou

2013-01-01

Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels. For example, an image can be represented as a bag of segments and associated with a list of objects it contains. Prior work on MIML has focused on predicting label sets for previously unseen...

RAZVOJ OBLAČIL V HIP HOP KULTURI

OpenAIRE

Marić, Sanja

2010-01-01

V diplomskem delu smo raziskovali, kako so se hip hop oblačila razvijala skozi obdobja v hip hop kulturi. V teoretičnem deli smo ugotavljali ozadje in dejavnike, ki so vplivali na razvoj hip hop kulture, v empiričnem delu diplomske naloge pa smo izvedli anketni vprašalnik z glavnimi akterji hip hop kulture na slovenski hip hop sceni. Rezultati, ki smo jih dobili, kažejo da so imela oblačila velik vpliv na prepoznavnost in razvoj hip hop kulture po celem svetu. K temu so največ pripomogli ustv...

Collective Machine Learning: Team Learning and Classification in Multi-Agent Systems

Science.gov (United States)

Gifford, Christopher M.

2009-01-01

This dissertation focuses on the collaboration of multiple heterogeneous, intelligent agents (hardware or software) which collaborate to learn a task and are capable of sharing knowledge. The concept of collaborative learning in multi-agent and multi-robot systems is largely under studied, and represents an area where further research is needed to…

From "They" Science to "Our" Science: Hip Hop Epistemology in STEAM Education

Science.gov (United States)

Dolberry, Maurice E.

Hip hop has moved from being considered a type of music into being understood as a culture in which a prominent type of music originates. Hip hop culture has a philosophy and epistemological constructs as well. This study analyzed those constructs to determine how conceptions of science factor in hip hop worldviews. Pedagogical models in culturally responsive teaching and Science, Technology, Engineering, Arts, and Mathematics (STEAM) education were also examined to discern their philosophical connections with hip hop culture. These connections were used to create two theoretical models. The first one, Hip Hop Science, described how scientific thought functions in hip hop culture. The second model, Hip Hop STEAM Pedagogy, proposes how hip hop culture can inform STEAM teaching practices. The study began by using Critical Race Theory to create a theoretical framework proposing how the two theoretical models could be derived from the philosophical and pedagogical concepts. Content analysis and narrative inquiry were used to analyze data collected from scholarly texts, hip hop songs, and interviews with hip hop-responsive educators. The data from these sources were used initially to assess the adequacy of the proposed theoretical framework, and subsequently to improve its viability. Four overlapping themes emerged from the data analyses, including hip hop-resistance to formal education; how hip hop culture informs pedagogical practice in hip hop-responsive classrooms; conceptions of knowledge and reality that shape how hip hoppers conduct scientific inquiry; and hip hop-based philosophies of effective teaching for hip hoppers as a marginalized cultural group. The findings indicate that there are unique connections between hip hop epistemology, sciencemindedness, and pedagogical practices in STEAM education. The revised theoretical framework clarified the nature of these connections, and supported claims from prior research that hip hop culture provides viable sites of

A Jackson network model and threshold policy for joint optimization of energy and delay in multi-hop wireless networks

KAUST Repository

Xia, Li; Shihada, Basem

2014-01-01

This paper studies the joint optimization problem of energy and delay in a multi-hop wireless network. The optimization variables are the transmission rates, which are adjustable according to the packet queueing length in the buffer. The optimization goal is to minimize the energy consumption of energy-critical nodes and the packet transmission delay throughout the network. In this paper, we aim at understanding the well-known decentralized algorithms which are threshold based from a different research angle. By using a simplified network model, we show that we can adopt the semi-open Jackson network model and study this optimization problem in closed form. This simplified network model further allows us to establish some significant optimality properties. We prove that the system performance is monotonic with respect to (w.r.t.) the transmission rate. We also prove that the threshold-type policy is optimal, i.e., when the number of packets in the buffer is larger than a threshold, transmit with the maximal rate (power); otherwise, no transmission. With these optimality properties, we develop a heuristic algorithm to iteratively find the optimal threshold. Finally, we conduct some simulation experiments to demonstrate the main idea of this paper.

A Jackson network model and threshold policy for joint optimization of energy and delay in multi-hop wireless networks

KAUST Repository

Xia, Li

2014-11-20

This paper studies the joint optimization problem of energy and delay in a multi-hop wireless network. The optimization variables are the transmission rates, which are adjustable according to the packet queueing length in the buffer. The optimization goal is to minimize the energy consumption of energy-critical nodes and the packet transmission delay throughout the network. In this paper, we aim at understanding the well-known decentralized algorithms which are threshold based from a different research angle. By using a simplified network model, we show that we can adopt the semi-open Jackson network model and study this optimization problem in closed form. This simplified network model further allows us to establish some significant optimality properties. We prove that the system performance is monotonic with respect to (w.r.t.) the transmission rate. We also prove that the threshold-type policy is optimal, i.e., when the number of packets in the buffer is larger than a threshold, transmit with the maximal rate (power); otherwise, no transmission. With these optimality properties, we develop a heuristic algorithm to iteratively find the optimal threshold. Finally, we conduct some simulation experiments to demonstrate the main idea of this paper.

Minimum Information Loss Based Multi-kernel Learning for Flagellar Protein Recognition in Trypanosoma Brucei

KAUST Repository

Wang, Jim Jing-Yan

2014-12-01

Trypanosma brucei (T. Brucei) is an important pathogen agent of African trypanosomiasis. The flagellum is an essential and multifunctional organelle of T. Brucei, thus it is very important to recognize the flagellar proteins from T. Brucei proteins for the purposes of both biological research and drug design. In this paper, we investigate computationally recognizing flagellar proteins in T. Brucei by pattern recognition methods. It is argued that an optimal decision function can be obtained as the difference of probability functions of flagella protein and the non-flagellar protein for the purpose of flagella protein recognition. We propose to learn a multi-kernel classification function to approximate this optimal decision function, by minimizing the information loss of such approximation which is measured by the Kull back-Leibler (KL) divergence. An iterative multi-kernel classifier learning algorithm is developed to minimize the KL divergence for the problem of T. Brucei flagella protein recognition, experiments show its advantage over other T. Brucei flagellar protein recognition and multi-kernel learning methods. © 2014 IEEE.

Distributed Generation Planning using Peer Enhanced Multi-objective Teaching-Learning based Optimization in Distribution Networks

Science.gov (United States)

Selvam, Kayalvizhi; Vinod Kumar, D. M.; Siripuram, Ramakanth

2017-04-01

In this paper, an optimization technique called peer enhanced teaching learning based optimization (PeTLBO) algorithm is used in multi-objective problem domain. The PeTLBO algorithm is parameter less so it reduced the computational burden. The proposed peer enhanced multi-objective based TLBO (PeMOTLBO) algorithm has been utilized to find a set of non-dominated optimal solutions [distributed generation (DG) location and sizing in distribution network]. The objectives considered are: real power loss and the voltage deviation subjected to voltage limits and maximum penetration level of DG in distribution network. Since the DG considered is capable of injecting real and reactive power to the distribution network the power factor is considered as 0.85 lead. The proposed peer enhanced multi-objective optimization technique provides different trade-off solutions in order to find the best compromise solution a fuzzy set theory approach has been used. The effectiveness of this proposed PeMOTLBO is tested on IEEE 33-bus and Indian 85-bus distribution system. The performance is validated with Pareto fronts and two performance metrics (C-metric and S-metric) by comparing with robust multi-objective technique called non-dominated sorting genetic algorithm-II and also with the basic TLBO.

The Formation of "Hip-Hop Academicus"--How American Scholars Talk about the Academisation of Hip-Hop

Science.gov (United States)

Soderman, Johan

2013-01-01

Social activism and education have been associated with hip-hop since it emerged in New York City 38 years ago. Therefore, it might not be surprising that universities have become interested in hip-hop. This article aims to highlight this "hip-hop academisation" and analyse the discursive mechanisms that manifest in these academisation…

Radio resource management scheme and outage analysis for network-assisted multi-hop D2D communications

OpenAIRE

Leila Melki; Sameh Najeh; Hichem Besbes

2016-01-01

In a cellular network it's very difficult to make spectrum resource more efficiently. Device-to-Device (D2D) technology enables new service opportunities, and provides high throughput and reliable communication while reducing the base station load. For better total performance, short-range D2D links and cellular links share the same radio resource and the management of interference becomes a crucial task. Here we argue that single-hop D2D technology can be used to further improve cellular net...

Variable range hopping in ZnO films

Science.gov (United States)

Ali, Nasir; Ghosh, Subhasis

2018-04-01

We report the variable range hopping in ZnO films grown by RF magnetron sputtering in different argon and oxygen partial pressure. It has been found that Mott variable range hopping dominant over Efros variable range hopping in all ZnO films. It also has been found that hopping distance and energy increases with increasing oxygen partial pressure.

Hip-Hop--What's in It for the Academy? Self-Understanding, Pedagogy and Aesthetical Learning Processes in Everyday Cultural Praxis

Science.gov (United States)

Söderman, Johan; Sernhede, Ove

2016-01-01

Since hip-hop first appeared in New York over 35 years ago, it has been associated with social activism and education. Accordingly, it is not surprising that academic institutions in universities and K-12 schools are interested in hip-hop. In this article, we will highlight the "hip-hop academisation" and map out a new direction in a…

Multi-instance dictionary learning via multivariate performance measure optimization

KAUST Repository

Wang, Jim Jing-Yan

2016-12-29

The multi-instance dictionary plays a critical role in multi-instance data representation. Meanwhile, different multi-instance learning applications are evaluated by specific multivariate performance measures. For example, multi-instance ranking reports the precision and recall. It is not difficult to see that to obtain different optimal performance measures, different dictionaries are needed. This observation motives us to learn performance-optimal dictionaries for this problem. In this paper, we propose a novel joint framework for learning the multi-instance dictionary and the classifier to optimize a given multivariate performance measure, such as the F1 score and precision at rank k. We propose to represent the bags as bag-level features via the bag-instance similarity, and learn a classifier in the bag-level feature space to optimize the given performance measure. We propose to minimize the upper bound of a multivariate loss corresponding to the performance measure, the complexity of the classifier, and the complexity of the dictionary, simultaneously, with regard to both the dictionary and the classifier parameters. In this way, the dictionary learning is regularized by the performance optimization, and a performance-optimal dictionary is obtained. We develop an iterative algorithm to solve this minimization problem efficiently using a cutting-plane algorithm and a coordinate descent method. Experiments on multi-instance benchmark data sets show its advantage over both traditional multi-instance learning and performance optimization methods.

Multi-instance dictionary learning via multivariate performance measure optimization

KAUST Repository

Wang, Jim Jing-Yan; Tsang, Ivor Wai-Hung; Cui, Xuefeng; Lu, Zhiwu; Gao, Xin

2016-01-01

The multi-instance dictionary plays a critical role in multi-instance data representation. Meanwhile, different multi-instance learning applications are evaluated by specific multivariate performance measures. For example, multi-instance ranking reports the precision and recall. It is not difficult to see that to obtain different optimal performance measures, different dictionaries are needed. This observation motives us to learn performance-optimal dictionaries for this problem. In this paper, we propose a novel joint framework for learning the multi-instance dictionary and the classifier to optimize a given multivariate performance measure, such as the F1 score and precision at rank k. We propose to represent the bags as bag-level features via the bag-instance similarity, and learn a classifier in the bag-level feature space to optimize the given performance measure. We propose to minimize the upper bound of a multivariate loss corresponding to the performance measure, the complexity of the classifier, and the complexity of the dictionary, simultaneously, with regard to both the dictionary and the classifier parameters. In this way, the dictionary learning is regularized by the performance optimization, and a performance-optimal dictionary is obtained. We develop an iterative algorithm to solve this minimization problem efficiently using a cutting-plane algorithm and a coordinate descent method. Experiments on multi-instance benchmark data sets show its advantage over both traditional multi-instance learning and performance optimization methods.

Hall effect in hopping regime

International Nuclear Information System (INIS)

Avdonin, A.; Skupiński, P.; Grasza, K.

2016-01-01

A simple description of the Hall effect in the hopping regime of conductivity in semiconductors is presented. Expressions for the Hall coefficient and Hall mobility are derived by considering averaged equilibrium electron transport in a single triangle of localization sites in a magnetic field. Dependence of the Hall coefficient is analyzed in a wide range of temperature and magnetic field values. Our theoretical result is applied to our experimental data on temperature dependence of Hall effect and Hall mobility in ZnO. - Highlights: • Expressions for Hall coefficient and mobility for hopping conductivity are derived. • Theoretical result is compared with experimental curves measured on ZnO. • Simultaneous action of free and hopping conduction channels is considered. • Non-linearity of hopping Hall coefficient is predicted.

Hall effect in hopping regime

Energy Technology Data Exchange (ETDEWEB)

Avdonin, A., E-mail: avdonin@ifpan.edu.pl [Institute of Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warszawa (Poland); Skupiński, P. [Institute of Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warszawa (Poland); Grasza, K. [Institute of Physics, Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warszawa (Poland); Institute of Electronic Materials Technology, ul. Wólczyńska 133, 01-919 Warszawa (Poland)

2016-02-15

A simple description of the Hall effect in the hopping regime of conductivity in semiconductors is presented. Expressions for the Hall coefficient and Hall mobility are derived by considering averaged equilibrium electron transport in a single triangle of localization sites in a magnetic field. Dependence of the Hall coefficient is analyzed in a wide range of temperature and magnetic field values. Our theoretical result is applied to our experimental data on temperature dependence of Hall effect and Hall mobility in ZnO. - Highlights: • Expressions for Hall coefficient and mobility for hopping conductivity are derived. • Theoretical result is compared with experimental curves measured on ZnO. • Simultaneous action of free and hopping conduction channels is considered. • Non-linearity of hopping Hall coefficient is predicted.

Manifold regularized matrix completion for multi-label learning with ADMM.

Science.gov (United States)

Liu, Bin; Li, Yingming; Xu, Zenglin

2018-05-01

Multi-label learning is a common machine learning problem arising from numerous real-world applications in diverse fields, e.g, natural language processing, bioinformatics, information retrieval and so on. Among various multi-label learning methods, the matrix completion approach has been regarded as a promising approach to transductive multi-label learning. By constructing a joint matrix comprising the feature matrix and the label matrix, the missing labels of test samples are regarded as missing values of the joint matrix. With the low-rank assumption of the constructed joint matrix, the missing labels can be recovered by minimizing its rank. Despite its success, most matrix completion based approaches ignore the smoothness assumption of unlabeled data, i.e., neighboring instances should also share a similar set of labels. Thus they may under exploit the intrinsic structures of data. In addition, the matrix completion problem can be less efficient. To this end, we propose to efficiently solve the multi-label learning problem as an enhanced matrix completion model with manifold regularization, where the graph Laplacian is used to ensure the label smoothness over it. To speed up the convergence of our model, we develop an efficient iterative algorithm, which solves the resulted nuclear norm minimization problem with the alternating direction method of multipliers (ADMM). Experiments on both synthetic and real-world data have shown the promising results of the proposed approach. Copyright © 2018 Elsevier Ltd. All rights reserved.

A review on machine learning principles for multi-view biological data integration.

Science.gov (United States)

Li, Yifeng; Wu, Fang-Xiang; Ngom, Alioune

2018-03-01

Driven by high-throughput sequencing techniques, modern genomic and clinical studies are in a strong need of integrative machine learning models for better use of vast volumes of heterogeneous information in the deep understanding of biological systems and the development of predictive models. How data from multiple sources (called multi-view data) are incorporated in a learning system is a key step for successful analysis. In this article, we provide a comprehensive review on omics and clinical data integration techniques, from a machine learning perspective, for various analyses such as prediction, clustering, dimension reduction and association. We shall show that Bayesian models are able to use prior information and model measurements with various distributions; tree-based methods can either build a tree with all features or collectively make a final decision based on trees learned from each view; kernel methods fuse the similarity matrices learned from individual views together for a final similarity matrix or learning model; network-based fusion methods are capable of inferring direct and indirect associations in a heterogeneous network; matrix factorization models have potential to learn interactions among features from different views; and a range of deep neural networks can be integrated in multi-modal learning for capturing the complex mechanism of biological systems.

Time and Energy Efficient Relay Transmission for Multi-Hop Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jin-Woo Kim

2016-06-01

Full Text Available The IEEE 802.15.4 standard is widely recognized as one of the most successful enabling technologies for short range low rate wireless communications and it is used in IoT applications. It covers all the details related to the MAC and PHY layers of the IoT protocol stack. Due to the nature of IoT, the wireless sensor networks are autonomously self-organized networks without infrastructure support. One of the issues in IoT is the network scalability. To address this issue, it is necessary to support the multi-hop topology. The IEEE 802.15.4 network can support a star, peer-to-peer, or cluster-tree topology. One of the IEEE 802.15.4 topologies suited for the high predictability of performance guarantees and energy efficient behavior is a cluster-tree topology where sensor nodes can switch off their transceivers and go into a sleep state to save energy. However, the IEEE 802.15.4 cluster-tree topology may not be able to provide sufficient bandwidth for the increased traffic load and the additional information may not be delivered successfully. The common drawback of the existing approaches is that they do not address the poor bandwidth utilization problem in IEEE 802.15.4 cluster-tree networks, so it is difficult to increase the network performance. Therefore, to solve this problem in this paper we study a relay transmission protocol based on the standard protocol in the IEEE 802.15.4 MAC. In the proposed scheme, the coordinators can relay data frames to their parent devices or their children devices without contention and can provide bandwidth for the increased traffic load or the number of devices. We also evaluate the performance of the proposed scheme through simulation. The simulation results demonstrate that the proposed scheme can improve the reliability, the end-to-end delay, and the energy consumption.

Injury incidence in hip hop dance.

Science.gov (United States)

Ojofeitimi, S; Bronner, S; Woo, H

2012-06-01

Hip hop dance has rapidly become a popular international art form. There is limited information on injury patterns in this population. The purpose of this study was to determine injury incidence and patterns among three groups of hip hop dancers. Three hundred and twelve intermediate, advanced, and expert hip hop dancers were recruited at battles, dance conferences, clubs, and on dance related web sites within the United States and internationally. A Web-based survey was conducted over a 6-month period. Inclusion criteria included intermediate and advanced level dancers over the age of 13. Dancers were divided into three main categories: Breakers, Popper/Lockers, and New Schoolers. Separate analysis of variances were used to compare injury pattern differences between groups. Two hundred and thirty-two dancers reported a total of 738 injuries. Five hundred and six of these (sustained by 205 dancers) were time-loss (TL) injuries. Annual injury incidence was 237% (162% involving TL). Lower extremity injuries were 52% and upper extremity injuries 32% of total injuries. Breakers had a higher injury incidence compared with Popper/Lockers, and New Schoolers. Hip hop dancers report injury rates that are higher than other dance forms but similar to gymnastics. These dancers should be educated concerning injury prevention, biomechanics, and use of protective equipment. © 2010 John Wiley & Sons A/S.

Hops

Science.gov (United States)

... The effectiveness ratings for HOPS are as follows:Body odor. Early research suggests that applying a deodorant that ... specific zinc salt to the underarm can reduce body odor. Insomnia. Some research suggests that taking a combination ...

"Dear Tupac, You Speak to Me": Recruiting Hip Hop as Curriculum at a School for Pregnant and Parenting Teens

Science.gov (United States)

Hallman, Heidi L.

2009-01-01

This article provides a rich representation of how in-school practices that recruit students' "out-of-school" literacies, such as hip hop, can be used as critical bridges in students' learning. Hip hop, conceptualized in this article as an "out-of-school" literacy, works as a vehicle for curricular change at Eastview School for Pregnant and…

Supercritical carbon dioxide hop extraction

Directory of Open Access Journals (Sweden)

Pfaf-Šovljanski Ivana I.

2005-01-01

Full Text Available The hop of Magnum cultivar was extracted using supercritical carbon dioxide (SFE-as extractant. Extraction was carried out in the two steps: the first one being carried out at 150 bar and 40°C for 2.5 h (Extract A, and the second was the extraction of the same hop sample at 300 bar and 40°C for 2.5 h (Extract B. Extraction kinetics of the system hop-SFE-CO2 was investigated. Two of four most common compounds of hop aroma (α-humulene and β-caryophyllene were detected in Extract A. Isomerised α-acids and β-acids were detected too. a-Acid content in Extract B was high (that means it is a bitter variety of hop. Mathematical modeling using empirical model characteristic time model and simple single sphere model has been performed on Magnum cultivar extraction experimental results. Characteristic time model equations, best fitted experimental results. Empirical model equation, fitted results well, while simple single sphere model equation poorly approximated the results.

The small GTPase Arl8b regulates assembly of the mammalian HOPS complex on lysosomes

Science.gov (United States)

Khatter, Divya; Raina, Vivek B.; Dwivedi, Devashish; Sindhwani, Aastha; Bahl, Surbhi; Sharma, Mahak

2015-01-01

The homotypic fusion and protein sorting (HOPS) complex is a multi-subunit complex conserved from yeast to mammals that regulates late endosome and lysosome fusion. However, little is known about how the HOPS complex is recruited to lysosomes in mammalian cells. Here, we report that the small GTPase Arl8b, but not Rab7 (also known as RAB7A), is essential for membrane localization of the human (h)Vps41 subunit of the HOPS complex. Assembly of the core HOPS subunits to Arl8b- and hVps41-positive lysosomes is guided by their subunit–subunit interactions. RNA interference (RNAi)-mediated depletion of hVps41 resulted in the impaired degradation of EGFR that was rescued upon expression of wild-type but not an Arl8b-binding-defective mutant of hVps41, suggesting that Arl8b-dependent lysosomal localization of hVps41 is required for its endocytic function. Furthermore, we have also identified that the Arl8b effector SKIP (also known as PLEKHM2) interacts with and recruits HOPS subunits to Arl8b and kinesin-positive peripheral lysosomes. Accordingly, RNAi-mediated depletion of SKIP impaired lysosomal trafficking and degradation of EGFR. These findings reveal that Arl8b regulates the association of the human HOPS complex with lysosomal membranes, which is crucial for the function of this tethering complex in endocytic degradation. PMID:25908847

The small GTPase Arl8b regulates assembly of the mammalian HOPS complex on lysosomes.

Science.gov (United States)

Khatter, Divya; Raina, Vivek B; Dwivedi, Devashish; Sindhwani, Aastha; Bahl, Surbhi; Sharma, Mahak

2015-05-01

The homotypic fusion and protein sorting (HOPS) complex is a multi-subunit complex conserved from yeast to mammals that regulates late endosome and lysosome fusion. However, little is known about how the HOPS complex is recruited to lysosomes in mammalian cells. Here, we report that the small GTPase Arl8b, but not Rab7 (also known as RAB7A), is essential for membrane localization of the human (h)Vps41 subunit of the HOPS complex. Assembly of the core HOPS subunits to Arl8b- and hVps41-positive lysosomes is guided by their subunit-subunit interactions. RNA interference (RNAi)-mediated depletion of hVps41 resulted in the impaired degradation of EGFR that was rescued upon expression of wild-type but not an Arl8b-binding-defective mutant of hVps41, suggesting that Arl8b-dependent lysosomal localization of hVps41 is required for its endocytic function. Furthermore, we have also identified that the Arl8b effector SKIP (also known as PLEKHM2) interacts with and recruits HOPS subunits to Arl8b and kinesin-positive peripheral lysosomes. Accordingly, RNAi-mediated depletion of SKIP impaired lysosomal trafficking and degradation of EGFR. These findings reveal that Arl8b regulates the association of the human HOPS complex with lysosomal membranes, which is crucial for the function of this tethering complex in endocytic degradation. © 2015. Published by The Company of Biologists Ltd.

Cultivated grapevines represent a symptomless reservoir for the transmission of hop stunt viroid to hop crops: 15 years of evolutionary analysis.

Directory of Open Access Journals (Sweden)

Yoko Kawaguchi-Ito

Full Text Available Hop stunt was a mysterious disorder that first emerged in the 1940s in commercial hops in Japan. To investigate the origin of this disorder, we infected hops with natural Hop stunt viroid (HpSVd isolates derived from four host species (hop, grapevine, plum and citrus, which except for hop represent possible sources of the ancestral viroid. These plants were maintained for 15 years, then analyzed the HpSVd variants present. Here we show that the variant originally found in cultivated grapevines gave rise to various combinations of mutations at positions 25, 26, 54, 193, and 281. However, upon prolonged infection, these variants underwent convergent evolution resulting in a limited number of adapted mutants. Some of them showed nucleotide sequences identical to those currently responsible for hop stunt epidemics in commercial hops in Japan, China, and the United States. Therefore, these results indicate that we have successfully reproduced the original process by which a natural HpSVd variant naturally introduced into cultivated hops was able to mutate into the HpSVd variants that are currently present in commercial hops. Furthermore, and importantly, we have identified cultivated grapevines as a symptomless reservoir in which HSVd can evolve and be transmitted to hop crops to cause epidemics.

Hip-Hop Education Resources

Science.gov (United States)

Hall, Marcella Runell

2009-01-01

Hip-hop music and culture are often cited as being public pedagogy, meaning the music itself has intrinsic educational value. Non-profit organizations and individual educators have graciously taken the lead in utilizing hip-hop to educate. As the academy continues to debate its effectiveness, teachers and community organizers are moving forward.…

A very general rate expression for charge hopping in semiconducting polymers

Energy Technology Data Exchange (ETDEWEB)

Fornari, Rocco P.; Aragó, Juan; Troisi, Alessandro [Department of Chemistry and Centre for Scientific Computing, University of Warwick, Coventry CV4 7AL (United Kingdom)

2015-05-14

We propose an expression of the hopping rate between localized states in semiconducting disordered polymers that contain the most used rates in the literature as special cases. We stress that these rates cannot be obtained directly from electron transfer rate theories as it is not possible to define diabatic localized states if the localization is caused by disorder, as in most polymers, rather than nuclear polarization effects. After defining the separate classes of accepting and inducing nuclear modes in the system, we obtain a general expression of the hopping rate. We show that, under the appropriate limits, this expression reduces to (i) a single-phonon rate expression or (ii) the Miller-Abrahams rate or (iii) a multi-phonon expression. The description of these limits from a more general expression is useful to interpolate between them, to validate the assumptions of each limiting case, and to define the simplest rate expression that still captures the main features of the charge transport. When the rate expression is fed with a range of realistic parameters the deviation from the Miller-Abrahams rate is large or extremely large, especially for hopping toward lower energy states, due to the energy gap law.

Fast Hopping Frequency Generation in Digital CMOS

CERN Document Server

Farazian, Mohammad; Gudem, Prasad S

2013-01-01

Overcoming the agility limitations of conventional frequency synthesizers in multi-band OFDM ultra wideband is a key research goal in digital technology. This volume outlines a frequency plan that can generate all the required frequencies from a single fixed frequency, able to implement center frequencies with no more than two levels of SSB mixing. It recognizes the need for future synthesizers to bypass on-chip inductors and operate at low voltages to enable the increased integration and efficiency of networked appliances. The author examines in depth the architecture of the dividers that generate the necessary frequencies from a single base frequency and are capable of establishing a fractional division ratio.   Presenting the first CMOS inductorless single PLL 14-band frequency synthesizer for MB-OFDMUWB makes this volume a key addition to the literature, and with the synthesizer capable of arbitrary band-hopping in less than two nanoseconds, it operates well within the desired range on a 1.2-volt power s...

Highly Efficient Multi Channel Packet Forwarding with Round Robin Intermittent Periodic Transmit for Multihop Wireless Backhaul Networks

Science.gov (United States)

Furukawa, Hiroshi

2017-01-01

Round Robin based Intermittent Periodic Transmit (RR-IPT) has been proposed which achieves highly efficient multi-hop relays in multi-hop wireless backhaul networks (MWBN) where relay nodes are 2-dimensionally deployed. This paper newly investigates multi-channel packet scheduling and forwarding scheme for RR-IPT. Downlink traffic is forwarded by RR-IPT via one of the channels, while uplink traffic and part of downlink are accommodated in the other channel. By comparing IPT and carrier sense multiple access with collision avoidance (CSMA/CA) for uplink/downlink packet forwarding channel, IPT is more effective in reducing packet loss rate whereas CSMA/CA is better in terms of system throughput and packet delay improvement. PMID:29137164

Deep learning for classification of islanding and grid disturbance based on multi-resolution singular spectrum entropy

Science.gov (United States)

Li, Tie; He, Xiaoyang; Tang, Junci; Zeng, Hui; Zhou, Chunying; Zhang, Nan; Liu, Hui; Lu, Zhuoxin; Kong, Xiangrui; Yan, Zheng

2018-02-01

Forasmuch as the distinguishment of islanding is easy to be interfered by grid disturbance, island detection device may make misjudgment thus causing the consequence of photovoltaic out of service. The detection device must provide with the ability to differ islanding from grid disturbance. In this paper, the concept of deep learning is introduced into classification of islanding and grid disturbance for the first time. A novel deep learning framework is proposed to detect and classify islanding or grid disturbance. The framework is a hybrid of wavelet transformation, multi-resolution singular spectrum entropy, and deep learning architecture. As a signal processing method after wavelet transformation, multi-resolution singular spectrum entropy combines multi-resolution analysis and spectrum analysis with entropy as output, from which we can extract the intrinsic different features between islanding and grid disturbance. With the features extracted, deep learning is utilized to classify islanding and grid disturbance. Simulation results indicate that the method can achieve its goal while being highly accurate, so the photovoltaic system mistakenly withdrawing from power grids can be avoided.

Risk Assessment Using The Homeland-Defense Operational Planning System (HOPS)

International Nuclear Information System (INIS)

Price, D E; Durling, R L

2005-01-01

The Homeland-Defense Operational Planning System (HOPS), is a new operational planning tool leveraging Lawrence Livermore National Laboratory's expertise in weapons systems and in sparse information analysis to support the defense of the U.S. homeland. HOPS provides planners with a basis to make decisions to protect against acts of terrorism, focusing on the defense of facilities critical to U.S. infrastructure. Criticality of facilities, structures, and systems is evaluated on a composite matrix of specific projected casualty, economic, and sociopolitical impact bins. Based on these criteria, significant unidentified vulnerabilities are identified and secured. To provide insight into potential successes by malevolent actors, HOPS analysts strive to base their efforts mainly on unclassified open-source data. However, more cooperation is needed between HOPS analysts and facility representatives to provide an advantage to those whose task is to defend these facilities. Evaluated facilities include: refineries, major ports, nuclear power plants and other nuclear licensees, dams, government installations, convention centers, sports stadiums, tourist venues, and public and freight transportation systems. A generalized summary of analyses of U.S. infrastructure facilities will be presented

Switched diversity strategies for dual-hop relaying systems

KAUST Repository

Gaaloul, Fakhreddine

2011-04-29

This paper investigates the effect of different switched diversity configurations on the implementation complexity and achieved performance of dual-hop amplify-and-forward (AF) relaying networks. A low-complexity model of the relay station is adopted, wherein single-input single-output antenna configuration is employed. Each of the transmitter and the receiver however employs multiple antennas to improve the overall link performance. Single-phase and two-phase based receive switching strategies are investigated assuming optimum first hop signal-to-noise ratio (SNR). Moreover, the simple scheme in which the switched diversity is applied independently over the two hops is studied using tight upper bounds. Thorough performance comparisons and switching thresholds optimization for the aforementioned strategies are presented. Simulation results are also provided to validate the mathematical development and to verify the numerical computations.

Multi-Gateway-Based Energy Holes Avoidance Routing Protocol for WSN

Directory of Open Access Journals (Sweden)

Rohini Sharma

2016-04-01

Full Text Available In wireless sensor networks (WSNs, efficient energy conservation is required to prolong the lifetime of the network. In this work, we have given emphasis on balanced energy consumption and energy holes avoidance. This paper proposes a multi-gateway-based approach to reduce the transmission distance between the sender and the sink node. The area to be monitored is divided into regions and gateway nodes are deployed at optimal positions. We have designed a transmission scheme, in which sensors in the sink region communicate directly to the sink, sensors in the gateway region communicate directly to the gateway, and sensors in the cluster region transmit their data directly to their respective cluster head which transmits data to the gateway in its region. If the distance between a cluster head and the sink is less than the distance between the cluster head and the gateway node, the cluster head transmits data to the sink instead of the gateway node. We have compared the proposed protocol with Low-Energy Adaptive Clustering Hierarchy (LEACH, Gateway Based Energy Aware Multi-Hop Routing (M-GEAR, and Gateway Based Stable Election Protocol (GSEP protocols. The protocol performs better than other protocols in terms of throughput, stability period, lifetime, residual energy, and the packet transmitted to the sink.

Hip-Hop and the Academic Canon

Science.gov (United States)

Abe, Daudi

2009-01-01

Over the last 30 years, the hip-hop movement has risen from the margins to become the preeminent force in US popular culture. In more recent times academics have begun to harness the power of hip-hop culture and use it as a means of infusing transformative knowledge into the mainstream academic discourse. On many college campuses, hip-hop's…

Fundamentals of beer and hop chemistry

Directory of Open Access Journals (Sweden)

Denis De Keukeleire

2000-02-01

Full Text Available Beer brewing is an intricate process encompassing mixing and further elaboration of four essential raw materials, including barley malt, brewing water, hops and yeast. Particularly hops determine to a great extent typical beer qualities such as bitter taste, hoppy flavour, and foam stability. Conversely, hop-derived bitter acids account for an offending lightstruck flavour, which is formed on exposure of beer to light. These various processes are presented in detail, while due emphasis is placed on state-of-the-art hop technology, which provides brewers with efficient means to control bitterness, foam, and light-stability thereby allowing for the production of beers with consistent quality.

A modified teaching–learning based optimization for multi-objective optimal power flow problem

International Nuclear Information System (INIS)

Shabanpour-Haghighi, Amin; Seifi, Ali Reza; Niknam, Taher

2014-01-01

Highlights: • A new modified teaching–learning based algorithm is proposed. • A self-adaptive wavelet mutation strategy is used to enhance the performance. • To avoid reaching a large repository size, a fuzzy clustering technique is used. • An efficiently smart population selection is utilized. • Simulations show the superiority of this algorithm compared with other ones. - Abstract: In this paper, a modified teaching–learning based optimization algorithm is analyzed to solve the multi-objective optimal power flow problem considering the total fuel cost and total emission of the units. The modified phase of the optimization algorithm utilizes a self-adapting wavelet mutation strategy. Moreover, a fuzzy clustering technique is proposed to avoid extremely large repository size besides a smart population selection for the next iteration. These techniques make the algorithm searching a larger space to find the optimal solutions while speed of the convergence remains good. The IEEE 30-Bus and 57-Bus systems are used to illustrate performance of the proposed algorithm and results are compared with those in literatures. It is verified that the proposed approach has better performance over other techniques

Multi Car Elevator Control by using Learning Automaton

Science.gov (United States)

Shiraishi, Kazuaki; Hamagami, Tomoki; Hirata, Hironori

We study an adaptive control technique for multi car elevators (MCEs) by adopting learning automatons (LAs.) The MCE is a high performance and a near-future elevator system with multi shafts and multi cars. A strong point of the system is that realizing a large carrying capacity in small shaft area. However, since the operation is too complicated, realizing an efficient MCE control is difficult for top-down approaches. For example, “bunching up together" is one of the typical phenomenon in a simple traffic environment like the MCE. Furthermore, an adapting to varying environment in configuration requirement is a serious issue in a real elevator service. In order to resolve these issues, having an autonomous behavior is required to the control system of each car in MCE system, so that the learning automaton, as the solutions for this requirement, is supposed to be appropriate for the simple traffic control. First, we assign a stochastic automaton (SA) to each car control system. Then, each SA varies its stochastic behavior distributions for adapting to environment in which its policy is evaluated with each passenger waiting times. That is LA which learns the environment autonomously. Using the LA based control technique, the MCE operation efficiency is evaluated through simulation experiments. Results show the technique enables reducing waiting times efficiently, and we confirm the system can adapt to the dynamic environment.

Powerful Tests for Multi-Marker Association Analysis Using Ensemble Learning.

Directory of Open Access Journals (Sweden)

Badri Padhukasahasram

Full Text Available Multi-marker approaches have received a lot of attention recently in genome wide association studies and can enhance power to detect new associations under certain conditions. Gene-, gene-set- and pathway-based association tests are increasingly being viewed as useful supplements to the more widely used single marker association analysis which have successfully uncovered numerous disease variants. A major drawback of single-marker based methods is that they do not look at the joint effects of multiple genetic variants which individually may have weak or moderate signals. Here, we describe novel tests for multi-marker association analyses that are based on phenotype predictions obtained from machine learning algorithms. Instead of assuming a linear or logistic regression model, we propose the use of ensembles of diverse machine learning algorithms for prediction. We show that phenotype predictions obtained from ensemble learning algorithms provide a new framework for multi-marker association analysis. They can be used for constructing tests for the joint association of multiple variants, adjusting for covariates and testing for the presence of interactions. To demonstrate the power and utility of this new approach, we first apply our method to simulated SNP datasets. We show that the proposed method has the correct Type-1 error rates and can be considerably more powerful than alternative approaches in some situations. Then, we apply our method to previously studied asthma-related genes in 2 independent asthma cohorts to conduct association tests.

Pertunjukan Teater Karo Hip Hop Kontemporer KAI

Directory of Open Access Journals (Sweden)

Silvia Anggreni Purba

2013-11-01

Pertunjukan Teater Karo Hip Hop Kontemporer KAI. The performance of Karo Theater collaborated with Hip Hop stems from a simple idea to collaborate Karo cultural traditions with popular culture. The performances can be enjoyed without having limitation on the language and culture. The process of combining two different cultures is a form of hybrid culture, and it may occur due to the globalization process. Through the process of deposition of the observations and strong impression, this performance is then brought into the form of Hip Hop as a preferred form which is energetic, personal and global. This performance is part of a modern tragedy with its destructive character which has explored the emotion and has presented it to the audiences. The exploration of Karo cultural tradition and Hip Hop dance as a language of symbols is able to reinforce words. The movement is not revealed by the verbal phrase but is presented through the movement of Hip Hop dance. The interpretation of the legend and texts into movement is carried out through the training process at the laboratory as a searching process and experiment, and afterward can be realized by considering the basic elements of Hip Hop, Karo cultural elements and performance. Karo Hip Hop Theatre is expected to become a preferred aesthetic form of a modern theater without losing its tradition form. Keyword: a contemporary Karo theater, Hip Hop, hybrid culture.

Concurrent Learning of Control in Multi agent Sequential Decision Tasks

Science.gov (United States)

2018-04-17

Concurrent Learning of Control in Multi-agent Sequential Decision Tasks The overall objective of this project was to develop multi-agent reinforcement... learning (MARL) approaches for intelligent agents to autonomously learn distributed control policies in decentral- ized partially observable... learning of policies in Dec-POMDPs, established performance bounds, evaluated these algorithms both theoretically and empirically, The views

Hip-hop and urban studies

NARCIS (Netherlands)

Jaffe, R.

2014-01-01

How can urban studies research engage fruitfully with hip-hop? This contribution responds to the essays by David Beer and Martin Lamotte on ‘street music’, urban ethnography and ghettoized communities. It discusses how a social science engagement with hip-hop texts might differ from cultural studies

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

Science.gov (United States)

Ferreria, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

2017-01-01

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

Multi-task feature learning by using trace norm regularization

Directory of Open Access Journals (Sweden)

Jiangmei Zhang

2017-11-01

Full Text Available Multi-task learning can extract the correlation of multiple related machine learning problems to improve performance. This paper considers applying the multi-task learning method to learn a single task. We propose a new learning approach, which employs the mixture of expert model to divide a learning task into several related sub-tasks, and then uses the trace norm regularization to extract common feature representation of these sub-tasks. A nonlinear extension of this approach by using kernel is also provided. Experiments conducted on both simulated and real data sets demonstrate the advantage of the proposed approach.

THE EFFECTS OF SINGLE LEG HOP PROGRESSION AND DOUBLE LEGS HOP PROGRESSION EXERCISE TO INCREASE SPEED AND EXPLOSIVE POWER OF LEG MUSCLE

Directory of Open Access Journals (Sweden)

Nining W. Kusnanik

2015-05-01

Full Text Available The main purpose of this study was to determine the effect of single leg hop progression and double legs hop progression exercise to increase speed and explosive power of leg muscles. Plyometric is one of the training methods that can increase explosive power. There are many models of plyometric training including single leg hop progression and double leg hop progression. This research was experimental using match subject design techniques. The subjects of this study were 39 students who joined basketball school club. There were 3 groups in this study: Group 1 were 13 students who given sin¬gle leg hop progression exercise, Group 2 were 13 students who given double legs hop progression exercise, Group 3 were 13 students who given conventional exercise. The data was collected during pre test and post test by testing 30m speed running and vertical jump. The data was analyzed using Analysis of Varians (Anova. It was found that there were significantly increased on speed and explosive power of leg muscles of Group 1 and Group 2. It can be stated that single leg hop progression exercise was more effective than double leg hop progression exercise. The recent findings supported the hypothesis that single leg hop progression and double legs hop progression exercise can increase speed and explosive power of leg muscles. These finding were supported by some previous studies (Singh, et al, 2011; Shallaby, H.K., 2010. The single leg hop progression is more effective than double legs hop progression. This finding was consistent with some previous evidences (McCurdy, et al, 2005; Makaruk et al, 2011.

Horror Image Recognition Based on Context-Aware Multi-Instance Learning.

Science.gov (United States)

Li, Bing; Xiong, Weihua; Wu, Ou; Hu, Weiming; Maybank, Stephen; Yan, Shuicheng

2015-12-01

Horror content sharing on the Web is a growing phenomenon that can interfere with our daily life and affect the mental health of those involved. As an important form of expression, horror images have their own characteristics that can evoke extreme emotions. In this paper, we present a novel context-aware multi-instance learning (CMIL) algorithm for horror image recognition. The CMIL algorithm identifies horror images and picks out the regions that cause the sensation of horror in these horror images. It obtains contextual cues among adjacent regions in an image using a random walk on a contextual graph. Borrowing the strength of the fuzzy support vector machine (FSVM), we define a heuristic optimization procedure based on the FSVM to search for the optimal classifier for the CMIL. To improve the initialization of the CMIL, we propose a novel visual saliency model based on the tensor analysis. The average saliency value of each segmented region is set as its initial fuzzy membership in the CMIL. The advantage of the tensor-based visual saliency model is that it not only adaptively selects features, but also dynamically determines fusion weights for saliency value combination from different feature subspaces. The effectiveness of the proposed CMIL model is demonstrated by its use in horror image recognition on two large-scale image sets collected from the Internet.

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.

Science.gov (United States)

Zhang, Xin; Yan, Lin-Feng; Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-07-18

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization.

A multi-label learning based kernel automatic recommendation method for support vector machine.

Science.gov (United States)

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

The Simulation Computer Based Learning (SCBL) for Short Circuit Multi Machine Power System Analysis

Science.gov (United States)

Rahmaniar; Putri, Maharani

2018-03-01

Strengthening Competitiveness of human resources become the reply of college as a conductor of high fomal education. Electrical Engineering Program UNPAB (Prodi TE UNPAB) as one of the department of electrical engineering that manages the field of electrical engineering expertise has a very important part in preparing human resources (HR), Which is required by where graduates are produced by DE UNPAB, Is expected to be able to compete globally, especially related to the implementation of Asean Economic Community (AEC) which requires the active participation of graduates with competence and quality of human resource competitiveness. Preparation of HR formation Competitive is done with the various strategies contained in the Seven (7) Higher Education Standard, one part of which is the implementation of teaching and learning process in Electrical system analysis with short circuit analysis (SCA) This course is a course The core of which is the basis for the competencies of other subjects in the advanced semester at Development of Computer Based Learning model (CBL) is done in the learning of interference analysis of multi-machine short circuit which includes: (a) Short-circuit One phase, (B) Two-phase Short Circuit Disruption, (c) Ground Short Circuit Disruption, (d) Short Circuit Disruption One Ground Floor Development of CBL learning model for Electrical System Analysis course provides space for students to be more active In learning in solving complex (complicated) problems, so it is thrilling Ilkan flexibility of student learning how to actively solve the problem of short-circuit analysis and to form the active participation of students in learning (Student Center Learning, in the course of electrical power system analysis.

Majorana edge States in atomic wires coupled by pair hopping.

Science.gov (United States)

Kraus, Christina V; Dalmonte, Marcello; Baranov, Mikhail A; Läuchli, Andreas M; Zoller, P

2013-10-25

We present evidence for Majorana edge states in a number conserving theory describing a system of spinless fermions on two wires that are coupled by pair hopping. Our analysis is based on a combination of a qualitative low energy approach and numerical techniques using the density matrix renormalization group. In addition, we discuss an experimental realization of pair-hopping interactions in cold atom gases confined in optical lattices.

Wavelength-Hopping Time-Spreading Optical CDMA With Bipolar Codes

Science.gov (United States)

Kwong, Wing C.; Yang, Guu-Chang; Chang, Cheng-Yuan

2005-01-01

Two-dimensional wavelength-hopping time-spreading coding schemes have been studied recently for supporting greater numbers of subscribers and simultaneous users than conventional one-dimensional approaches in optical code-division multiple-access (OCDMA) systems. To further improve both numbers without sacrificing performance, a new code design utilizing bipolar codes for both wavelength hopping and time spreading is studied and analyzed in this paper. A rapidly programmable, integratable hardware design for this new coding scheme, based on arrayed-waveguide gratings, is also discussed.

Fasilitas Pelatihan dan Pergelaran Seni Tari Hip Hop di Surabaya

OpenAIRE

Yanuar, Sandy

2014-01-01

Fasilitas Pelatihan dan Pergelaran Seni Tari Hip Hop di Surabaya merupakan fasilitas yang disediakan bagi semua penari Hip Hop di Surabaya untuk berlatih menari dan mempertunjukan tarian Hip Hop. Fasilitas ini tersedia bagi semua penari Hip Hop termasuk penari difable, mengingat kaum difable juga dapat menari Hip Hop. Namun karena di Surabaya belum memiliki fasilitas yang memadai bagi semua penari Hip Hop termasuk penari difable untuk menari dan memiliki tempat pertunjukan yang berkarakter Hi...

A Multi-Faceted Approach to Inquiry-Based Learning

Science.gov (United States)

Brudzinski, M. R.; Sikorski, J.

2009-12-01

In order to fully attain the benefits of inquiry-based learning, instructors who typically employ the traditional lecture format need to make several adjustments to their approach. This change in styles can be intimidating and logistically difficult to overcome. A stepwise approach to this transformation is likely to be more manageable for individual faculty or departments. In this session, we will describe several features that we are implementing in our introductory geology course with the ultimate goal of converting to an entirely inquiry-based approach. Our project is part of the Miami University initiative in the top 25 enrolled courses to move towards the “student as scholar” model for engaged learning. Some of the features we developed for our course include: student learning outcomes, student development outcomes, out-of-class content quizzes, in-class conceptests, pre-/post-course assessment, reflective knowledge surveys, and daily group activities.

Electronic and vibrational hopping transport in boron carbides

International Nuclear Information System (INIS)

Emin, D.

1991-01-01

General concepts of hopping-type transport and localization are reviewed. Disorder, electronic correlations and atomic displacements, effects ignored in electronic band structure calculations, foster localization of electronic charge carriers. Examples are given that illustrate the efficacy of these effects in producing localization. This introduction is followed by a brief discussion of the relation between hopping-type transport and localization. The fundamentals of the formation, localization, and hopping transport of small polarons and/or bipolarons is then described. Electronic transport in boron carbides is presented as an example of the adiabatic hopping of small bipolarons. Finally, the notion of vibrational hopping is introduced. The high-temperature thermal diffusion in boron carbides is presented as a potential application of this idea

HIP HOP for HIV Awareness: Using Hip Hop Culture to Promote Community-Level HIV Prevention

Science.gov (United States)

Hill, Mandy J.; Hallmark, Camden J.; McNeese, Marlene; Blue, Nike; Ross, Michael W.

2014-01-01

The goal of this paper was to determine the effectiveness of the HIP HOP for HIV Awareness intervention, an innovative model utilising an exchange of an HIV test for a hip hop concert ticket, in a metropolitan city among African American youth and young adults. A subset of intervention participants participated in standardised testing, sex…

Hip-Hop Culture in College Students' Lives: Elements, Embodiment, and Higher Edutainment

Science.gov (United States)

Petchauer, Emery

2011-01-01

College campuses have become rich sites of hip-hop culture and knowledge production. Despite the attention that campus personnel and researchers have paid to student life, the field of higher education has often misunderstood the ways that hip-hop culture exists in college students' lives. Based upon in-depth interviews, observations of…

Unified Multi-Layer among Software Defined Multi-Domain Optical Networks (Invited

Directory of Open Access Journals (Sweden)

Hui Yang

2015-06-01

Full Text Available The software defined networking (SDN enabled by OpenFlow protocol has gained popularity which can enable the network to be programmable and accommodate both fixed and flexible bandwidth services. In this paper, we present a unified multi-layer (UML architecture with multiple controllers and a dynamic orchestra plane (DOP for software defined multi-domain optical networks. The proposed architecture can shield the differences among various optical devices from multi-vendors and the details of connecting heterogeneous networks. The cross-domain services with on-demand bandwidth can be deployed via unified interfaces provided by the dynamic orchestra plane. Additionally, the globalization strategy and practical capture of signal processing are presented based on the architecture. The overall feasibility and efficiency of the proposed architecture is experimentally verified on the control plane of our OpenFlow-based testbed. The performance of globalization strategy under heavy traffic load scenario is also quantitatively evaluated based on UML architecture compared with other strategies in terms of blocking probability, average hops, and average resource consumption.

Online multi-modal robust non-negative dictionary learning for visual tracking.

Science.gov (United States)

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

KAUST Repository

Alharbi, Basma Mohammed; Zhang, Xiangliang

2017-01-01

Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals's mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users' check-ins and their network of friends, without impairing the model's complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

KAUST Repository

Alharbi, Basma Mohammed

2017-02-07

Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals\\'s mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users\\' check-ins and their network of friends, without impairing the model\\'s complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

Hip external rotation strength predicts hop performance after anterior cruciate ligament reconstruction.

Science.gov (United States)

Kline, Paul W; Burnham, Jeremy; Yonz, Michael; Johnson, Darren; Ireland, Mary Lloyd; Noehren, Brian

2018-04-01

operative limb compared to the control and non-operative limbs, even after starting sport-specific drills. Importantly, HER strength independently predicted hop performance. Based on these findings, to resolve between-limb deficits in strength and hop performance clinicians should include HER strengthening exercises in post-operative rehabilitation. Prognostic Study, Level II.

Supporting Communication and Argumentation in Urban Science Education: Hip-Hop, the Battle, and the Cypher

Science.gov (United States)

Emdin, Christopher

2011-01-01

This paper is based on an exploration of communication and argumentation in urban science classrooms, and provides a description of the role that Hip-hop based education plays in supporting these major components of science education. The paper is intended to both support, and critique conventional uses of hip-hop based education, and provide…

On the role of cost-sensitive learning in multi-class brain-computer interfaces.

Science.gov (United States)

Devlaminck, Dieter; Waegeman, Willem; Wyns, Bart; Otte, Georges; Santens, Patrick

2010-06-01

Brain-computer interfaces (BCIs) present an alternative way of communication for people with severe disabilities. One of the shortcomings in current BCI systems, recently put forward in the fourth BCI competition, is the asynchronous detection of motor imagery versus resting state. We investigated this extension to the three-class case, in which the resting state is considered virtually lying between two motor classes, resulting in a large penalty when one motor task is misclassified into the other motor class. We particularly focus on the behavior of different machine-learning techniques and on the role of multi-class cost-sensitive learning in such a context. To this end, four different kernel methods are empirically compared, namely pairwise multi-class support vector machines (SVMs), two cost-sensitive multi-class SVMs and kernel-based ordinal regression. The experimental results illustrate that ordinal regression performs better than the other three approaches when a cost-sensitive performance measure such as the mean-squared error is considered. By contrast, multi-class cost-sensitive learning enables us to control the number of large errors made between two motor tasks.

Use of the Homeland-Defense Operational Planning System (HOPS) for Emergency Management

International Nuclear Information System (INIS)

Durling, Jr. R.L.; Price, D.E.

2005-01-01

The Homeland-Defense Operational Planning System (HOPS), is a new operational planning tool leveraging Lawrence Livermore National Laboratory's expertise in weapons systems and in sparse information analysis to support the defense of the U.S. homeland. HOPS provides planners with a basis to make decisions to protect against acts of terrorism, focusing on the defense of facilities critical to U.S. infrastructure. Criticality of facilities, structures, and systems is evaluated on a composite matrix of specific projected casualty, economic, and sociopolitical impact bins. Based on these criteria, significant unidentified vulnerabilities are identified and secured. To provide insight into potential successes by malevolent actors, HOPS analysts strive to base their efforts mainly on unclassified open-source data. However, more cooperation is needed between HOPS analysts and facility representatives to provide an advantage to those whose task is to defend these facilities. Evaluated facilities include: refineries, major ports, nuclear power plants and other nuclear licensees, dams, government installations, convention centers, sports stadiums, tourist venues, and public and freight transportation systems. A generalized summary of analyses of U.S. infrastructure facilities will be presented

Hybrid E-Learning Tool TransLearning: Video Storytelling to Foster Vicarious Learning within Multi-Stakeholder Collaboration Networks

Science.gov (United States)

van der Meij, Marjoleine G.; Kupper, Frank; Beers, Pieter J.; Broerse, Jacqueline E. W.

2016-01-01

E-learning and storytelling approaches can support informal vicarious learning within geographically widely distributed multi-stakeholder collaboration networks. This case study evaluates hybrid e-learning and video-storytelling approach "TransLearning" by investigation into how its storytelling e-tool supported informal vicarious…

Antimicrobial activity of hop extracts against foodborne pathogens for meat applications.

Science.gov (United States)

Kramer, B; Thielmann, J; Hickisch, A; Muranyi, P; Wunderlich, J; Hauser, C

2015-03-01

The objective of this study was the fundamental investigation of the antimicrobial efficiency of various hop extracts against selected foodborne pathogens in vitro, as well as their activity against Listeria monocytogenes in a model meat marinade and on marinated pork tenderloins. In a first step, the minimum inhibitory concentrations (MIC) of three hop extracts containing either α- or β-acids or xanthohumol were determined against test bacteria including L. monocytogenes, Staphylococcus aureus, Salmonella enterica and Escherichia coli by a colorimetric method based on the measurement of bacterial metabolic activity. Moreover, the influence of either lactic or citric acid on the antimicrobial activity of the hop extracts was evaluated. The efficiency of hop extracts as a natural food preservative was then tested in a model meat marinade at 2 and 8°C, respectively, and finally on marinated pork. The experiments showed that Gram-positive bacteria were strongly inhibited by hop extracts containing β-acids and xanthohumol (MIC values of 6.3 and 12.5 ppm, respectively), whereas the antimicrobial activity of the investigated α-acid extract was significantly lower (MIC values of 200 ppm). Gram-negative bacteria were highly resistant against all tested hop extracts. Acidification of the test media led to a decrease of the MIC values. The inhibitory activity of the hop extracts against L. monocytogenes was strongly reduced in a fat-containing model meat marinade, but the efficiency of β-acids in this matrix could be increased by lowering pH and storage temperatures. By applying 0.5 % β-acids at pH = 5 in a model marinade, the total aerobic count of pork tenderloins was reduced up to 0.9 log10 compared with marinated pork without hop extract after 2 weeks of storage at 5°C. β-acid containing hop extracts have proven to possess a high antimicrobial activity against Gram-positive bacteria in vitro and in a practice-related application for food preservation

LINKS: learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images.

Science.gov (United States)

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-03-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. Copyright © 2014 Elsevier Inc. All rights reserved.

Development of multi-representation learning tools for the course of fundamental physics

Science.gov (United States)

Huda, C.; Siswanto, J.; Kurniawan, A. F.; Nuroso, H.

2016-08-01

This research is aimed at designing a learning tool based on multi-representation that can improve problem solving skills. It used the research and development approach. It was applied for the course of Fundamental Physics at Universitas PGRI Semarang for the 2014/2015 academic year. Results show gain analysis value of 0.68, which means some medium improvements. The result of t-test is shows a calculated value of 27.35 and a table t of 2.020 for df = 25 and α = 0.05. Results of pre-tests and post-tests increase from 23.45 to 76.15. Application of multi-representation learning tools significantly improves students’ grades.

GHz band frequency hopping PLL-based frequency synthesizers

Institute of Scientific and Technical Information of China (English)

XU Yong; WANG Zhi-gong; GUAN Yu; XU Zhi-jun; QIAO Lu-feng

2005-01-01

In this paper we describe a full-integrated circuit containing all building blocks of a completed PLL-based synthesizer except for low pass filter(LPF).The frequency synthesizer is designed for a frequency hopping (FH) transceiver operating up to 1.5 GHz as a local oscillator. The architecture of Voltage Controlled Oscillator (VCO) is optimized to get better performance, and a phase noise of -111.85-dBc/Hz @ 1 MHz and a tuning range of 250 MHz are gained at a centre frequency of 1.35 GHz.A novel Dual-Modulus Prescaler(DMP) is designed to achieve a very low jitter and a lower power.The settling time of PLL is 80 μs while the reference frequency is 400 KHz.This monolithic frequency synthesizer is to integrate all main building blocks of PLL except for the low pass filter,with a maximum VCO output frequency of 1.5 GHz,and is fabricated with a 0.18 μm mixed signal CMOS process. Low power dissipation, low phase noise, large tuning range and fast settling time are gained in this design.

Communication: Fully coherent quantum state hopping

Energy Technology Data Exchange (ETDEWEB)

Martens, Craig C., E-mail: cmartens@uci.edu [University of California, Irvine, California 92697-2025 (United States)

2015-10-14

In this paper, we describe a new and fully coherent stochastic surface hopping method for simulating mixed quantum-classical systems. We illustrate the approach on the simple but unforgiving problem of quantum evolution of a two-state quantum system in the limit of unperturbed pure state dynamics and for dissipative evolution in the presence of both stationary and nonstationary random environments. We formulate our approach in the Liouville representation and describe the density matrix elements by ensembles of trajectories. Population dynamics are represented by stochastic surface hops for trajectories representing diagonal density matrix elements. These are combined with an unconventional coherent stochastic hopping algorithm for trajectories representing off-diagonal quantum coherences. The latter generalizes the binary (0,1) “probability” of a trajectory to be associated with a given state to allow integers that can be negative or greater than unity in magnitude. Unlike existing surface hopping methods, the dynamics of the ensembles are fully entangled, correctly capturing the coherent and nonlocal structure of quantum mechanics.

Comparison of Rheological Properties of Hopped Wort and Malt Wort

Directory of Open Access Journals (Sweden)

Petr Trávníček

2015-01-01

Full Text Available The aim of this work is determination rheological properties of hopped wort and malt wort and their comparison. In the paper following rheological properties has been described: the dependence of viscosity on a temperature of a sample and hysteresis loop test. The time dependence test was performed for a confirmation thixotropic behaviour. Based on measured values Arrhenius mathematical model has been applied. The activation energy was determined by using of this model. Tests have been carried out in the temperature range from 5 °C to 40 °C. Rheological tests proved that malt wort behaves as Newtonian fluid in all temperatures and hopped wort behaves as non-Newtonian fluid at low temperatures. Thixotropic behaviour is caused by the content of the rests of hops heads or malt scraps.

What Is Hip-Hop-Based Education Doing in "Nice" Fields Such as Early Childhood and Elementary Education?

Science.gov (United States)

Love, Bettina L.

2015-01-01

Hip-Hop-Based Education (HHBE) has resulted in many positive educational outcomes, ranging from teaching academic skills to teaching critical reflection at secondary levels. Given what HHBE initiatives have accomplished, it is troubling that there is an absence of attention to these methods in education programs for elementary and early childhood…

Hip-Hop Is My Passport! Using Hip-Hop and Digital Literacies to Understand Global Citizenship Education

Science.gov (United States)

Horton, Akesha Monique

2013-01-01

Hip-hop has exploded around the world among youth. It is not simply an American source of entertainment; it is a global cultural movement that provides a voice for youth worldwide who have not been able to express their "cultural world" through mainstream media. The emerging field of critical hip-hop pedagogy has produced little…

Robust visual tracking via multi-task sparse learning

KAUST Repository

Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra

2012-01-01

In this paper, we formulate object tracking in a particle filter framework as a multi-task sparse learning problem, which we denote as Multi-Task Tracking (MTT). Since we model particles as linear combinations of dictionary templates

Designing electronic module based on learning content development system in fostering students’ multi representation skills

Science.gov (United States)

Resita, I.; Ertikanto, C.

2018-05-01

This study aims to develop electronic module design based on Learning Content Development System (LCDS) to foster students’ multi representation skills in physics subject material. This study uses research and development method to the product design. This study involves 90 students and 6 physics teachers who were randomly chosen from 3 different Senior High Schools in Lampung Province. The data were collected by using questionnaires and analyzed by using quantitative descriptive method. Based on the data, 95% of the students only use one form of representation in solving physics problems. Representation which is tend to be used by students is symbolic representation. Students are considered to understand the concept of physics if they are able to change from one form to the other forms of representation. Product design of LCDS-based electronic module presents text, image, symbolic, video, and animation representation.

Suppression of Plant Immune Responses by the Pseudomonas savastanoi pv. savastanoi NCPPB 3335 Type III Effector Tyrosine Phosphatases HopAO1 and HopAO2

Directory of Open Access Journals (Sweden)

María Pilar Castañeda-Ojeda

2017-05-01

Full Text Available The effector repertoire of the olive pathogen P. savastanoi pv. savastanoi NCPPB 3335 includes two members of the HopAO effector family, one of the most diverse T3E families of the P. syringae complex. The study described here explores the phylogeny of these dissimilar members, HopAO1 and HopAO2, among the complex and reveals their activities as immune defense suppressors. Although HopAO1 is predominantly encoded by phylogroup 3 strains isolated from woody organs of woody hosts, both HopAO1 and HopAO2 are phylogenetically clustered according to the woody/herbaceous nature of their host of isolation, suggesting host specialization of the HopAO family across the P. syringae complex. HopAO1 and HopAO2 translocate into plant cells and show hrpL-dependent expression, which allows their classification as actively deployed type III effectors. Our data also show that HopAO1 and HopAO2 possess phosphatase activity, a hallmark of the members of this family. Both of them exert an inhibitory effect on early plant defense responses, such as ROS production and callose deposition, and are able to suppress ETI responses induced by the effectorless polymutant of P. syringae pv. tomato DC3000 (DC3000D28E in Nicotiana. Moreover, we demonstrate that a ΔhopAO1 mutant of P. savastanoi NCPBB 3335 exhibits a reduced fitness and virulence in olive plants, which supports the relevance of this effector during the interaction of this strain with its host plants. This work contributes to the field with the first report regarding functional analysis of HopAO homologs encoded by P. syringae or P. savastanoi strains isolated from woody hosts.

Suppression of Plant Immune Responses by the Pseudomonas savastanoi pv. savastanoi NCPPB 3335 Type III Effector Tyrosine Phosphatases HopAO1 and HopAO2

Science.gov (United States)

Castañeda-Ojeda, María Pilar; Moreno-Pérez, Alba; Ramos, Cayo; López-Solanilla, Emilia

2017-01-01

The effector repertoire of the olive pathogen P. savastanoi pv. savastanoi NCPPB 3335 includes two members of the HopAO effector family, one of the most diverse T3E families of the P. syringae complex. The study described here explores the phylogeny of these dissimilar members, HopAO1 and HopAO2, among the complex and reveals their activities as immune defense suppressors. Although HopAO1 is predominantly encoded by phylogroup 3 strains isolated from woody organs of woody hosts, both HopAO1 and HopAO2 are phylogenetically clustered according to the woody/herbaceous nature of their host of isolation, suggesting host specialization of the HopAO family across the P. syringae complex. HopAO1 and HopAO2 translocate into plant cells and show hrpL-dependent expression, which allows their classification as actively deployed type III effectors. Our data also show that HopAO1 and HopAO2 possess phosphatase activity, a hallmark of the members of this family. Both of them exert an inhibitory effect on early plant defense responses, such as ROS production and callose deposition, and are able to suppress ETI responses induced by the effectorless polymutant of P. syringae pv. tomato DC3000 (DC3000D28E) in Nicotiana. Moreover, we demonstrate that a ΔhopAO1 mutant of P. savastanoi NCPBB 3335 exhibits a reduced fitness and virulence in olive plants, which supports the relevance of this effector during the interaction of this strain with its host plants. This work contributes to the field with the first report regarding functional analysis of HopAO homologs encoded by P. syringae or P. savastanoi strains isolated from woody hosts. PMID:28529516

Particle hopping vs. fluid-dynamical models for traffic flow

Energy Technology Data Exchange (ETDEWEB)

Nagel, K.

1995-12-31

Although particle hopping models have been introduced into traffic science in the 19509, their systematic use has only started recently. Two reasons for this are, that they are advantageous on modem computers, and that recent theoretical developments allow analytical understanding of their properties and therefore more confidence for their use. In principle, particle hopping models fit between microscopic models for driving and fluiddynamical models for traffic flow. In this sense, they also help closing the conceptual gap between these two. This paper shows connections between particle hopping models and traffic flow theory. It shows that the hydrodynamical limits of certain particle hopping models correspond to the Lighthill-Whitham theory for traffic flow, and that only slightly more complex particle hopping models produce already the correct traffic jam dynamics, consistent with recent fluid-dynamical models for traffic flow. By doing so, this paper establishes that, on the macroscopic level, particle hopping models are at least as good as fluid-dynamical models. Yet, particle hopping models have at least two advantages over fluid-dynamical models: they straightforwardly allow microscopic simulations, and they include stochasticity.

Effects of powdery mildew fungicide programs on twospotted spider mite (Acari: Tetranychidae), hop aphid (Hemiptera: Aphididae), and their natural enemies in hop yards.

Science.gov (United States)

Gent, D H; James, D G; Wright, L C; Brooks, D J; Barbour, J D; Dreves, A J; Fisher, G C; Walton, V M

2009-02-01

abundance in Washington was affected by fungicide treatments, with plots treated with sulfur consistently having 10-fold fewer phytoseiids per leaf compared with the other treatments. Based on the results of these studies, powdery mildew fungicide programs that minimize or eliminate applications of sulfur and paraffinic oil would tend to conserve predatory mites and minimize the severity of spider mite outbreaks. However, mechanisms other than direct or indirect toxicity to phytoseiid mites likely are associated with exacerbation of spider mite outbreaks on hop.

Multi-dimensional technology-enabled social learning approach

DEFF Research Database (Denmark)

Petreski, Hristijan; Tsekeridou, Sofia; Prasad, Neeli R.

2013-01-01

’t respond to this systemic and structural changes and/or challenges and retains its status quo than it is jeopardizing its own existence or the existence of the education, as we know it. This paper aims to precede one step further by proposing a multi-dimensional approach for technology-enabled social...... in learning while socializing within their learning communities. However, their “educational” usage is still limited to facilitation of online learning communities and to collaborative authoring of learning material complementary to existing formal (e-) learning services. If the educational system doesn...

The use of multi representative learning materials: definitive, macroscopic, microscopic, symbolic, and practice in analyzing students’ concept understanding

Science.gov (United States)

Susilaningsih, E.; Wulandari, C.; Supartono; Kasmui; Alighiri, D.

2018-03-01

This research aims to compose learning material which contains definitive macroscopic, microscopic and symbolic to analyze students’ conceptual understanding in acid-base learning materials. This research was conducted in eleven grade, natural science class, senior high school 1 (SMAN 1) Karangtengah, Demak province, Indonesia as the low level of students’ conceptual understanding and the high level of students’ misconception. The data collecting technique is by test to assess the cognitive aspect, questionnaire to assess students’ responses to multi representative learning materials (definitive, macroscopic, microscopic, symbolic), and observation to assess students’ macroscopic aspects. Three validators validate the multi-representative learning materials (definitive, macroscopic, microscopic, symbolic). The results of the research show that the multi-representative learning materials (definitive, macroscopic, microscopes, symbolic) being used is valid in the average score 62 of 75. The data is analyzed using the descriptive qualitative method. The results of the research show that 72.934 % students understand, 7.977 % less understand, 8.831 % do not understand, and 10.256 % misconception. In comparison, the second experiment class shows 54.970 % students understand, 5.263% less understand, 11.988 % do not understand, 27.777 % misconception. In conclusion, the application of multi representative learning materials (definitive, macroscopic, microscopic, symbolic) can be used to analyze the students’ understanding of acid-base materials.

High-Speed On-Board Data Processing for Science Instruments: HOPS

Science.gov (United States)

Beyon, Jeffrey

2015-01-01

The project called High-Speed On-Board Data Processing for Science Instruments (HOPS) has been funded by NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) program during April, 2012 â€" April, 2015. HOPS is an enabler for science missions with extremely high data processing rates. In this three-year effort of HOPS, Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) and 3-D Winds were of interest in particular. As for ASCENDS, HOPS replaces time domain data processing with frequency domain processing while making the real-time on-board data processing possible. As for 3-D Winds, HOPS offers real-time high-resolution wind profiling with 4,096-point fast Fourier transform (FFT). HOPS is adaptable with quick turn-around time. Since HOPS offers reusable user-friendly computational elements, its FPGA IP Core can be modified for a shorter development period if the algorithm changes. The FPGA and memory bandwidth of HOPS is 20 GB/sec while the typical maximum processor-to-SDRAM bandwidth of the commercial radiation tolerant high-end processors is about 130-150 MB/sec. The inter-board communication bandwidth of HOPS is 4 GB/sec while the effective processor-to-cPCI bandwidth of commercial radiation tolerant high-end boards is about 50-75 MB/sec. Also, HOPS offers VHDL cores for the easy and efficient implementation of ASCENDS and 3-D Winds, and other similar algorithms. A general overview of the 3-year development of HOPS is the goal of this presentation.

Hop-distance relationship analysis with quasi-UDG model for node localization in wireless sensor networks

Directory of Open Access Journals (Sweden)

Chen Ping

2011-01-01

Full Text Available Abstract In wireless sensor networks (WSNs, location information plays an important role in many fundamental services which includes geographic routing, target tracking, location-based coverage, topology control, and others. One promising approach in sensor network localization is the determination of location based on hop counts. A critical priori of this approach that directly influences the accuracy of location estimation is the hop-distance relationship. However, most of the related works on the hop-distance relationship assume the unit-disk graph (UDG model that is unrealistic in a practical scenario. In this paper, we formulate the hop-distance relationship for quasi-UDG model in WSNs where sensor nodes are randomly and independently deployed in a circular region based on a Poisson point process. Different from the UDG model, quasi-UDG model has the non-uniformity property for connectivity. We derive an approximated recursive expression for the probability of the hop count with a given geographic distance. The border effect and dependence problem are also taken into consideration. Furthermore, we give the expressions describing the distribution of distance with known hop counts for inner nodes and those suffered from the border effect where we discover the insignificance of the border effect. The analytical results are validated by simulations showing the accuracy of the employed approximation. Besides, we demonstrate the localization application of the formulated relationship and show the accuracy improvement in the WSN localization.

Complex Personhood of Hip Hop & the Sensibilities of the Culture That Fosters Knowledge of Self & Self-Determination

Science.gov (United States)

Love, Bettina L.

2016-01-01

Hip hop music and culture have a complex identity in that hip hop is based in self-determination, resistance, and the long enduring fight for Black freedom, but was also created alongside the seductiveness of the material and psychological conditions of capitalism, sexism, and patriarchy. Hip hop pedagogy (HHP) as a pedagogical framework is…

Generic Learning-Based Ensemble Framework for Small Sample Size Face Recognition in Multi-Camera Networks.

Science.gov (United States)

Zhang, Cuicui; Liang, Xuefeng; Matsuyama, Takashi

2014-12-08

Multi-camera networks have gained great interest in video-based surveillance systems for security monitoring, access control, etc. Person re-identification is an essential and challenging task in multi-camera networks, which aims to determine if a given individual has already appeared over the camera network. Individual recognition often uses faces as a trial and requires a large number of samples during the training phrase. This is difficult to fulfill due to the limitation of the camera hardware system and the unconstrained image capturing conditions. Conventional face recognition algorithms often encounter the "small sample size" (SSS) problem arising from the small number of training samples compared to the high dimensionality of the sample space. To overcome this problem, interest in the combination of multiple base classifiers has sparked research efforts in ensemble methods. However, existing ensemble methods still open two questions: (1) how to define diverse base classifiers from the small data; (2) how to avoid the diversity/accuracy dilemma occurring during ensemble. To address these problems, this paper proposes a novel generic learning-based ensemble framework, which augments the small data by generating new samples based on a generic distribution and introduces a tailored 0-1 knapsack algorithm to alleviate the diversity/accuracy dilemma. More diverse base classifiers can be generated from the expanded face space, and more appropriate base classifiers are selected for ensemble. Extensive experimental results on four benchmarks demonstrate the higher ability of our system to cope with the SSS problem compared to the state-of-the-art system.

Generic Learning-Based Ensemble Framework for Small Sample Size Face Recognition in Multi-Camera Networks

Directory of Open Access Journals (Sweden)

Cuicui Zhang

2014-12-01

Full Text Available Multi-camera networks have gained great interest in video-based surveillance systems for security monitoring, access control, etc. Person re-identification is an essential and challenging task in multi-camera networks, which aims to determine if a given individual has already appeared over the camera network. Individual recognition often uses faces as a trial and requires a large number of samples during the training phrase. This is difficult to fulfill due to the limitation of the camera hardware system and the unconstrained image capturing conditions. Conventional face recognition algorithms often encounter the “small sample size” (SSS problem arising from the small number of training samples compared to the high dimensionality of the sample space. To overcome this problem, interest in the combination of multiple base classifiers has sparked research efforts in ensemble methods. However, existing ensemble methods still open two questions: (1 how to define diverse base classifiers from the small data; (2 how to avoid the diversity/accuracy dilemma occurring during ensemble. To address these problems, this paper proposes a novel generic learning-based ensemble framework, which augments the small data by generating new samples based on a generic distribution and introduces a tailored 0–1 knapsack algorithm to alleviate the diversity/accuracy dilemma. More diverse base classifiers can be generated from the expanded face space, and more appropriate base classifiers are selected for ensemble. Extensive experimental results on four benchmarks demonstrate the higher ability of our system to cope with the SSS problem compared to the state-of-the-art system.

Research on synchronization technology of frequency hopping communication system

Science.gov (United States)

Zhao, Xiangwu; Quan, Houde; Cui, Peizhang

2018-05-01

Frequency Hopping (FH) communication is a technology of spread spectrum communication. It has strong anti-interference, anti-interception and security capabilities, and has been widely applied in the field of communications. Synchronization technology is one of the most crucial technologies in frequency hopping communication. The speed of synchronization establishment and the reliability of synchronous system directly affect the performance of frequency hopping communication system. Therefore, the research of synchronization technology in frequency hopping communication has important value.

Web-based Cooperative Learning in College Chemistry Teaching

Directory of Open Access Journals (Sweden)

Bin Jiang

2014-03-01

Full Text Available With the coming of information era, information process depend on internet and multi-media technology in education becomes the new approach of present teaching model reform. Web-based cooperative learning is becoming a popular learning approach with the rapid development of web technology. The paper aims to how to carry out the teaching strategy of web-based cooperative learning and applied in the foundation chemistry teaching.It was shown that with the support of modern web-based teaching environment, students' cooperative learning capacity and overall competence can be better improved and the problems of interaction in large foundation chemistry classes can be solved. Web-based cooperative learning can improve learning performance of students, what's more Web-based cooperative learning provides students with cooperative skills, communication skills, creativity, critical thinking skills and skills in information technology application.

A Lifetime Optimization Algorithm Limited by Data Transmission Delay and Hops for Mobile Sink-Based Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Yourong Chen

2017-01-01

Full Text Available To improve the lifetime of mobile sink-based wireless sensor networks and considering that data transmission delay and hops are limited in actual system, a lifetime optimization algorithm limited by data transmission delay and hops (LOA_DH for mobile sink-based wireless sensor networks is proposed. In LOA_DH, some constraints are analyzed, and an optimization model is proposed. Maximum capacity path routing algorithm is used to calculate the energy consumption of communication. Improved genetic algorithm which modifies individuals to meet all constraints is used to solve the optimization model. The optimal solution of sink node’s sojourn grid centers and sojourn times which maximizes network lifetime is obtained. Simulation results show that, in three node distribution scenes, LOA_DH can find the movement solution of sink node which covers all sensor nodes. Compared with MCP_RAND, MCP_GMRE, and EASR, the solution improves network lifetime and reduces average amount of node discarded data and average energy consumption of nodes.

Structure and DNA-binding of meiosis-specific protein Hop2

Science.gov (United States)

Zhou, Donghua; Moktan, Hem; Pezza, Roberto

2014-03-01

Here we report structure elucidation of the DNA binding domain of homologous pairing protein 2 (Hop2), which is important to gene diversity when sperms and eggs are produced. Together with another protein Mnd1, Hop2 enhances the strand invasion activity of recombinase Dmc1 by over 30 times, facilitating proper synapsis of homologous chromosomes. However, the structural and biochemical bases for the function of Hop2 and Mnd1 have not been well understood. As a first step toward such understanding, we recently solved the structure for the N-terminus of Hop2 (1-84) using solution NMR. This fragment shows a typical winged-head conformation with recognized DNA binding activity. DNA interacting sites were then investigated by chemical shift perturbations in a titration experiment. Information of these sites was used to guide protein-DNA docking with MD simulation, revealing that helix 3 is stably lodged in the DNA major groove and that wing 1 (connecting strands 2 and 3) transiently comes in contact with the minor groove in nanosecond time scale. Mutagenesis analysis further confirmed the DNA binding sites in this fragment of the protein.

Evaluation of PLC Channel Capacity and ABER Performances for OFDM-Based Two-Hop Relaying Transmission

Directory of Open Access Journals (Sweden)

Sana Ezzine

2017-01-01

Full Text Available Powerline network is recognized as a favorable infrastructure for Smart Grid to transmit information in the network thanks to its broad coverage and low cost deployment. The existing works are trying to improve and adapt transmission techniques to reduce Powerline Communication (PLC channel attenuation and exploit the limited bandwidth to support high data rate over long distances. Two-hop relaying BroadBand PLC (BB-PLC system, in which Orthogonal Frequency Division Multiplexing (OFDM is used, is considered in this paper. We derive and compare the PLC channel capacity and the end-to-end Average BER (ABER for OFDM-based direct link (DL BB-PLC system and for OFDM-based two-hop relaying BB-PLC system for Amplify and Forward (AF and Decode and Forward (DF protocols. We analyze the improvements when we consider the direct link in a cooperative communication when the relay node only transmits the correctly decoded signal. Maximum ratio combining is employed at the destination node to detect the transmitted signal. In addition, in this paper, we highlight the impact of the relay location on the channel capacity and ABER for AF and DF transmission protocols. Moreover, an efficient use of the direct link was also investigated in this paper.

SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

Directory of Open Access Journals (Sweden)

Zhang Xinzheng

2017-10-01

Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

Comparison of Low-Complexity Diversity Schemes for Dual-Hop AF Relaying Systems

KAUST Repository

Gaaloul, Fakhreddine

2012-02-13

This paper investigates the performance of two low-complexity combining schemes, which are based on one- or two-phase observation, to mitigate multipath fading in dual-hop amplify-and-forward relaying systems. For the one-phase-based combining, a single-antenna station is assumed to relay information from a multiple-antenna transmitter to a multiple-antenna receiver, and the activation of the receive antennas is adaptively performed based on the second-hop statistics, regardless of the first-hop conditions. On the other hand, the two-phase-based combining suggests using multiple single-antenna stations between the multiple-antenna transmitter and the single-antenna receiver, where the suitable set of active relays is identified according to the precombining end-to-end fading conditions. To facilitate comparisons between the two schemes, formulations for the statistics of the combined signal-to-noise ratio and some performance measures are presented. Numerical and simulation results are shown to clarify the tradeoff between the achieved diversity-array gain, the processing complexity, and the power consumption.

Real-Time On-Board Airborne Demonstration of High-Speed On-Board Data Processing for Science Instruments (HOPS)

Science.gov (United States)

Beyon, Jeffrey Y.; Ng, Tak-Kwong; Davis, Mitchell J.; Adams, James K.; Bowen, Stephen C.; Fay, James J.; Hutchinson, Mark A.

2015-01-01

The project called High-Speed On-Board Data Processing for Science Instruments (HOPS) has been funded by NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) program since April, 2012. The HOPS team recently completed two flight campaigns during the summer of 2014 on two different aircrafts with two different science instruments. The first flight campaign was in July, 2014 based at NASA Langley Research Center (LaRC) in Hampton, VA on the NASA's HU-25 aircraft. The science instrument that flew with HOPS was Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) CarbonHawk Experiment Simulator (ACES) funded by NASA's Instrument Incubator Program (IIP). The second campaign was in August, 2014 based at NASA Armstrong Flight Research Center (AFRC) in Palmdale, CA on the NASA's DC-8 aircraft. HOPS flew with the Multifunctional Fiber Laser Lidar (MFLL) instrument developed by Excelis Inc. The goal of the campaigns was to perform an end-to-end demonstration of the capabilities of the HOPS prototype system (HOPS COTS) while running the most computationally intensive part of the ASCENDS algorithm real-time on-board. The comparison of the two flight campaigns and the results of the functionality tests of the HOPS COTS are presented in this paper.

Plasmodium falciparum Hop (PfHop Interacts with the Hsp70 Chaperone in a Nucleotide-Dependent Fashion and Exhibits Ligand Selectivity.

Directory of Open Access Journals (Sweden)

Tawanda Zininga

Full Text Available Heat shock proteins (Hsps play an important role in the development and pathogenicity of malaria parasites. One of the most prominent functions of Hsps is to facilitate the folding of other proteins. Hsps are thought to play a crucial role when malaria parasites invade their host cells and during their subsequent development in hepatocytes and red blood cells. It is thought that Hsps maintain proteostasis under the unfavourable conditions that malaria parasites encounter in the host environment. Although heat shock protein 70 (Hsp70 is capable of independent folding of some proteins, its functional cooperation with heat shock protein 90 (Hsp90 facilitates folding of some proteins such as kinases and steroid hormone receptors into their fully functional forms. The cooperation of Hsp70 and Hsp90 occurs through an adaptor protein called Hsp70-Hsp90 organising protein (Hop. We previously characterised the Hop protein from Plasmodium falciparum (PfHop. We observed that the protein co-localised with the cytosol-localised chaperones, PfHsp70-1 and PfHsp90 at the blood stages of the malaria parasite. In the current study, we demonstrated that PfHop is a stress-inducible protein. We further explored the direct interaction between PfHop and PfHsp70-1 using far Western and surface plasmon resonance (SPR analyses. The interaction of the two proteins was further validated by co-immunoprecipitation studies. We observed that PfHop and PfHsp70-1 associate in the absence and presence of either ATP or ADP. However, ADP appears to promote the association of the two proteins better than ATP. In addition, we investigated the specific interaction between PfHop TPR subdomains and PfHsp70-1/ PfHsp90, using a split-GFP approach. This method allowed us to observe that TPR1 and TPR2B subdomains of PfHop bind preferentially to the C-terminus of PfHsp70-1 compared to PfHsp90. Conversely, the TPR2A motif preferentially interacted with the C-terminus of PfHsp90. Finally, we

Hopping models for ion conduction in noncrystals

DEFF Research Database (Denmark)

Dyre, Jeppe; Schrøder, Thomas

2007-01-01

semiconductors). These universalities are subject of much current interest, for instance interpreted in the context of simple hopping models. In the present paper we first discuss the temperature dependence of the dc conductivity in hopping models and the importance of the percolation phenomenon. Next......, the experimental (quasi)universality of the ac conductivity is discussed. It is shown that hopping models are able to reproduce the experimental finding that the response obeys time-temperature superposition, while at the same time a broad range of activation energies is involved in the conduction process. Again...

Risk Assessment Using The Homeland-Defense Operational Planning System (HOPS)

International Nuclear Information System (INIS)

Durling, R L; Price, D E; Spero, K K

2005-01-01

For over ten years, the Counterproliferation Analysis and Planning System (CAPS) at Lawrence Livermore National Laboratory (LLNL) has been a planning tool used by U.S. combatant commands for mission support planning against foreign programs engaged in the manufacture of weapons of mass destruction (WMD). CAPS is endorsed by the Secretary of Defense as the preferred counterproliferation tool to be used by the nation's armed services. A sister system, the Homeland-Defense Operational Planning System (HOPS), is a new operational planning tool leveraging CAPS expertise designed to support the defense of the U.S. homeland. HOPS provides planners with a basis to make decisions to protect against acts of terrorism, focusing on the defense of facilities critical to U.S. infrastructure. Criticality of facilities, structures, and systems is evaluated on a composite matrix of specific projected casualty, economic, and sociopolitical impact bins. Based on these criteria, significant unidentified vulnerabilities are identified and secured. To provide insight into potential successes by malevolent actors, HOPS analysts strive to base their efforts mainly on unclassified open-source data. However, more cooperation is needed between HOPS analysts and facility representatives to provide an advantage to those whose task is to defend these facilities. Evaluated facilities include: refineries, major ports, nuclear power plants and other nuclear licensees, dams, government installations, convention centers, sports stadiums, tourist venues, and public and freight transportation systems. A generalized summary of analyses of U.S. infrastructure facilities will be presented

Frequency hopping signal detection based on wavelet decomposition and Hilbert-Huang transform

Science.gov (United States)

Zheng, Yang; Chen, Xihao; Zhu, Rui

2017-07-01

Frequency hopping (FH) signal is widely adopted by military communications as a kind of low probability interception signal. Therefore, it is very important to research the FH signal detection algorithm. The existing detection algorithm of FH signals based on the time-frequency analysis cannot satisfy the time and frequency resolution requirement at the same time due to the influence of window function. In order to solve this problem, an algorithm based on wavelet decomposition and Hilbert-Huang transform (HHT) was proposed. The proposed algorithm removes the noise of the received signals by wavelet decomposition and detects the FH signals by Hilbert-Huang transform. Simulation results show the proposed algorithm takes into account both the time resolution and the frequency resolution. Correspondingly, the accuracy of FH signals detection can be improved.

How Does a Hopping Kangaroo Breathe?

Science.gov (United States)

Giuliodori, Mauricio J.; Lujan, Heidi L.; Janbaih, Hussein; DiCarlo, Stephen E.

2010-01-01

We developed a model to demonstrate how a hopping kangaroo breathes. Interestingly, a kangaroo uses less energy to breathe while hopping than while standing still. This occurs, in part, because rather than using muscle power to move air into and out of the lungs, air is pulled into (inspiration) and pushed out of (expiration) the lungs as the…

Model for using hip-hop music for small group HIV/AIDS prevention counseling with African American adolescents and young adults.

Science.gov (United States)

Stephens, T; Braithwaite, R L; Taylor, S E

1998-10-01

Currently little attention has been directed, with the exception of peer education efforts, to constructively develop new and innovative ways to promote HIV/AIDS primary prevention among African American (AA) adolescents and young adults. With this in mind, the aim of this conceptual effort is to present a HIV/AIDS preventive counseling protocol developed for use with AA young adults that makes use of hip-hop music, a form of music popularized by young AAs. The author contend that an increased understanding of the relationships that many AA young adults have with hip-hop music may be used by disease prevention personnel to educate these populations about protective factors for HIV. Making use of hip-hop music is one strategy for integrating counseling in prevention and health maintenance. The overall implications of using hip-hop music in health promotion are unlimited. First, this method makes use of cultural relevant materials to address the educational and health needs of the target community. Second, it is grounded in an approach that serves to stimulate cooperative learning based on peer developed content. Moreover, the use of this medium can be applied to other health promotion activities such as violence/harm reduction and substance abuse prevention, upon reviews of songs for appropriate content. The authors contend that such an approach holds heuristic value in dealing with HIV/AIDS prevention among AA young adults. Additional testing of the intervention is warranted in the refinement of this innovative intervention.

Suppression of hop looper (Lepidoptera: Noctuidae) by the fungicide pyraclostrobin.

Science.gov (United States)

Woods, J L; Gent, D H

2014-04-01

The hop looper, Hypena humuli Harris, is a reemergent pest of hop that often requires treatment to mitigate crop damage. In 4 yr of field trials, plots treated with fungicides were observed to sustain less hop looper defoliation compared with nontreated plots. Further investigation revealed that abundance of hop looper and associated defoliation were reduced when the fungicide pyraclostrobin was applied in late July to early August. Two other fungicides possessing active ingredients in the same chemical family (quinone outside inhibitor) did not reduce abundance of hop looper or its defoliation. Pyraclostrobin is efficacious against powdery mildew diseases, and the application timing evaluated in these studies corresponds with a period of juvenile susceptibility of hop cones to the disease. Use of fungicides containing pyraclostrobin at this time may have the ancillary benefit of reducing hop looper damage, potentially obviating the need for broad-spectrum insecticides later in the season. Follow-up studies are warranted to determine whether pyraclostrobin may inhibit other lepidopteran species.

The SAHR Setup-Controlling Hopping Speed and Height Using a Single Actuator

Directory of Open Access Journals (Sweden)

N. Cherouvim

2008-01-01

Full Text Available In this paper we present and experimentally validate a control method for regulating both the forward speed and the apex height of a one-legged hopping robot, using only a single actuator. The control method is based on a dynamic model of the hopping robot and makes use of the dynamic coupling of the vertical and forward motions of the robot. The control is applied first to a simulated model of the robot and shown to track a desired forward robot speed and a desired apex height. Then the SAHR (single actuator hopping robot hardware is introduced and is used as an experimental platform with which to evaluate the performance of the control method. The control method is applied to the physical setup and is shown to lead to a stable hopping gait with a desired forward speed and apex height, despite the unmodelled disturbances met on the laboratory floor.

Hip-Hopping across China: Intercultural Formulations of Local Identities

Science.gov (United States)

Barrett, Catrice

2012-01-01

The linguistic dimensions of globalized hip-hop cannot be understood simply as a byproduct of English as an American export. As hip-hop mobilizes, it is common (and arguably necessary) for global hip-hop communities to struggle through purposeful, semiotically rooted dialectics over what constitutes "authentic" and respectable forms of…

Using a multi-state Learning Community as an implementation strategy for immediate postpartum long-acting reversible contraception.

Science.gov (United States)

DeSisto, Carla L; Estrich, Cameron; Kroelinger, Charlan D; Goodman, David A; Pliska, Ellen; Mackie, Christine N; Waddell, Lisa F; Rankin, Kristin M

2017-11-21

Implementation strategies are imperative for the successful adoption and sustainability of complex evidence-based public health practices. Creating a learning collaborative is one strategy that was part of a recently published compilation of implementation strategy terms and definitions. In partnership with the Centers for Disease Control and Prevention and other partner agencies, the Association of State and Territorial Health Officials recently convened a multi-state Learning Community to support cross-state collaboration and provide technical assistance for improving state capacity to increase access to long-acting reversible contraception (LARC) in the immediate postpartum period, an evidence-based practice with the potential for reducing unintended pregnancy and improving maternal and child health outcomes. During 2015-2016, the Learning Community included multi-disciplinary, multi-agency teams of state health officials, payers, clinicians, and health department staff from 13 states. This qualitative study was conducted to better understand the successes, challenges, and strategies that the 13 US states in the Learning Community used for increasing access to immediate postpartum LARC. We conducted telephone interviews with each team in the Learning Community. Interviews were semi-structured and organized by the eight domains of the Learning Community. We coded transcribed interviews for facilitators, barriers, and implementation strategies, using a recent compilation of expert-defined implementation strategies as a foundation for coding the latter. Data analysis showed three ways that the activities of the Learning Community helped in policy implementation work: structure and accountability, validity, and preparing for potential challenges and opportunities. Further, the qualitative data demonstrated that the Learning Community integrated six other implementation strategies from the literature: organize clinician implementation team meetings, conduct

Approximate multi-state reliability expressions using a new machine learning technique

International Nuclear Information System (INIS)

Rocco S, Claudio M.; Muselli, Marco

2005-01-01

The machine-learning-based methodology, previously proposed by the authors for approximating binary reliability expressions, is now extended to develop a new algorithm, based on the procedure of Hamming Clustering, which is capable to deal with multi-state systems and any success criterion. The proposed technique is presented in details and verified on literature cases: experiment results show that the new algorithm yields excellent predictions

HapHop-Physio: a computer game to support cognitive therapies in children

Directory of Open Access Journals (Sweden)

Rico-Olarte C

2017-07-01

Full Text Available Carolina Rico-Olarte,1 Diego M López,1 Santiago Narváez,1 Charic D Farinango,1 Peter S Pharow2 1Faculty of Electronics and Telecommunications Engineering, Universidad del Cauca, Telematics Engineering Research Group, Popayán, Colombia; 2Fraunhofer Institute of Digital Media and Technology IDMT, Ilmenau, Germany Background: Care and support of children with physical or mental disabilities are accompanied with serious concerns for parents, families, healthcare institutions, schools, and their communities. Recent studies and technological innovations have demonstrated the feasibility of providing therapy and rehabilitation services to children supported by computer games. Objective: The aim of this paper is to present HapHop-Physio, an innovative computer game that combines exercise with fun and learning, developed to support cognitive therapies in children. Methods: Conventional software engineering methods such as the Scrum methodology, a functionality test and a related usability test, were part of the comprehensive methodology adapted to develop HapHop-Physio. Results: The game supports visual and auditory attention therapies, as well as visual and auditory memory activities. The game was developed by a multidisciplinary team, which was based on the Hopscotch® platform provided by Fraunhofer Institute for Digital Media Technology IDMT Institute in Germany, and designed in collaboration with a rehabilitation clinic in Colombia. HapHop-Physio was tested and evaluated to probe its functionality and user satisfaction. Conclusion: The results show the development of an easy-to-use and funny game by a multidisciplinary team using state-of-the-art videogame technologies and software methodologies. Children testing the game concluded that they would like to play again while undergoing rehabilitation therapies. Keywords: computer game, exer-games, cognitive therapies, rehabilitation

Characterization of hop pectins shows the presence of an arabinogalactan-protein

NARCIS (Netherlands)

Oosterveld, A.; Voragen, A.G.J.; Schols, H.A.

2002-01-01

Hop pectins were extracted from spent hops using acid extraction conditions and were characterized chemically. The acid extraction of spent hops resulted in a yield of 2°containing 59 f polysaccharides. The hop pectins under investigation had a relatively high molecular weight and an intrinsic

A decentralized scheduling algorithm for time synchronized channel hopping

Directory of Open Access Journals (Sweden)

Andrew Tinka

2011-09-01

Full Text Available Time Synchronized Channel Hopping (TSCH is an existing Medium Access Control scheme which enables robust communication through channel hopping and high data rates through synchronization. It is based on a time-slotted architecture, and its correct functioning depends on a schedule which is typically computed by a central node. This paper presents, to our knowledge, the first scheduling algorithm for TSCH networks which both is distributed and which copes with mobile nodes. Two variations on scheduling algorithms are presented. Aloha-based scheduling allocates one channel for broadcasting advertisements for new neighbors. Reservation- based scheduling augments Aloha-based scheduling with a dedicated timeslot for targeted advertisements based on gossip information. A mobile ad hoc motorized sensor network with frequent connectivity changes is studied, and the performance of the two proposed algorithms is assessed. This performance analysis uses both simulation results and the results of a field deployment of floating wireless sensors in an estuarial canal environment. Reservation-based scheduling performs significantly better than Aloha-based scheduling, suggesting that the improved network reactivity is worth the increased algorithmic complexity and resource consumption.

Hopping Conductivity Enhanced by Microwave Radiation

International Nuclear Information System (INIS)

Ovadyahu, Z

2012-01-01

Hopping conductivity is enhanced when exposed to microwave (MW) fields. Data taken on several Anderson-localized systems and granular-aluminium are presented to illustrate the generality of the phenomenon. It is suggested that the effect is due to a field-enhanced hopping, which is the ac version of a non-ohmic effect familiar from studies in the dc transport regime.

Secure Connectivity Probability of Multi‐hop Clustered Randomize‐and‐Forward Networks

Directory of Open Access Journals (Sweden)

Xiaowei Wang

2017-10-01

Full Text Available This work investigates secure cluster‐aided multi‐hop randomize‐and‐forward networks. We present a hop‐by‐hop multi‐hop transmission scheme with relay selection, which evaluates for each cluster the relays that can securely receive the message. We propose an analytical model to derive the secure connectivity probability (SCP of the hop‐by‐hop transmission scheme. For comparison, we also analyze SCPs of traditional end‐to‐end transmission schemes with two relay‐selection policies. We perform simulations, and our analytical results verify that the proposed hop‐by‐hop scheme is superior to end‐to‐end schemes, especially with a large number of hops or high eavesdropper channel quality. Numerical results also show that the proposed hop‐by‐hop scheme achieves near‐optimal performance in terms of the SCP.

Signaling induced by hop/STI-1 depends on endocytosis

International Nuclear Information System (INIS)

Americo, Tatiana A.; Chiarini, Luciana B.; Linden, Rafael

2007-01-01

The co-chaperone hop/STI-1 is a ligand of the cell surface prion protein (PrP C ), and their interaction leads to signaling and biological effects. Among these, hop/STI-1 induces proliferation of A172 glioblastoma cells, dependent on both PrP C and activation of the Erk pathway. We tested whether clathrin-mediated endocytosis affects signaling induced by hop/STI-1. Both hyperosmolarity induced by sucrose and monodansyl-cadaverine blocked Erk activity induced by hop/STI-1, without affecting the high basal Akt activity typical of A172. The endocytosis inhibitors also affected the sub-cellular distribution of phosphorylated Erk, consistent with blockade of the latter's activity. The data indicate that signaling induced by hop/STI-1 depends on endocytosis. These findings are consistent with a role of sub-cellular trafficking in signal transduction following engagement by PrP C by ligands such as hop/STI-1, and may help help unravel both the functions of the prion protein, as well as possible loss-of-function components of prion diseases

Multi-instance learning based on instance consistency for image retrieval

Science.gov (United States)

Zhang, Miao; Wu, Zhize; Wan, Shouhong; Yue, Lihua; Yin, Bangjie

2017-07-01

Multiple-instance learning (MIL) has been successfully utilized in image retrieval. Existing approaches cannot select positive instances correctly from positive bags which may result in a low accuracy. In this paper, we propose a new image retrieval approach called multiple instance learning based on instance-consistency (MILIC) to mitigate such issue. First, we select potential positive instances effectively in each positive bag by ranking instance-consistency (IC) values of instances. Then, we design a feature representation scheme, which can represent the relationship among bags and instances, based on potential positive instances to convert a bag into a single instance. Finally, we can use a standard single-instance learning strategy, such as the support vector machine, for performing object-based image retrieval. Experimental results on two challenging data sets show the effectiveness of our proposal in terms of accuracy and run time.

HPLC Analysis of [Alpha]- and [Beta]-Acids in Hops

Science.gov (United States)

Danenhower, Travis M.; Force, Leyna J.; Petersen, Kenneth J.; Betts, Thomas A.; Baker, Gary A.

2008-01-01

Hops have been used for centuries to impart aroma and bitterness to beer. The cones of the female hop plant contain both essential oils, which include many of the fragrant components of hops, and a collection of compounds known as [alpha]- and [beta]-acids that are the precursors to bittering agents. In order for brewers to predict the ultimate…

Biological and chemical standardization of a hop (Humulus lupulus) botanical dietary supplement.

Science.gov (United States)

Krause, Elizabeth; Yuan, Yang; Hajirahimkhan, Atieh; Dong, Huali; Dietz, Birgit M; Nikolic, Dejan; Pauli, Guido F; Bolton, Judy L; van Breemen, Richard B

2014-06-01

Concerned about the safety of conventional estrogen replacement therapy, women are using botanical dietary supplements as alternatives for the management of menopausal symptoms such as hot flashes. Before botanical dietary supplements can be evaluated clinically for safety and efficacy, botanically authenticated and standardized forms are required. To address the demand for a standardized, estrogenic botanical dietary supplement, an extract of hops (Humulus lupulus L.) was developed. Although valued in the brewing of beer, hop extracts are used as anxiolytics and hypnotics and have well-established estrogenic constituents. Starting with a hop cultivar used in the brewing industry, spent hops (the residue remaining after extraction of bitter acids) were formulated into a botanical dietary supplement that was then chemically and biologically standardized. Biological standardization utilized the estrogen-dependent induction of alkaline phosphatase in the Ishikawa cell line. Chemical standardization was based on the prenylated phenols in hops that included estrogenic 8-prenylnaringenin, its isomer 6-prenylnaringenin, and pro-estrogenic isoxanthohumol and its isomeric chalcone xanthohumol, all of which were measured using high-performance liquid chromatography-tandem mass spectrometry. The product of this process was a reproducible botanical extract suitable for subsequent investigations of safety and efficacy. Copyright © 2014 John Wiley & Sons, Ltd.

Asynchronous Channel-Hopping Scheme under Jamming Attacks

Directory of Open Access Journals (Sweden)

Yongchul Kim

2018-01-01

Full Text Available Cognitive radio networks (CRNs are considered an attractive technology to mitigate inefficiency in the usage of licensed spectrum. CRNs allow the secondary users (SUs to access the unused licensed spectrum and use a blind rendezvous process to establish communication links between SUs. In particular, quorum-based channel-hopping (CH schemes have been studied recently to provide guaranteed blind rendezvous in decentralized CRNs without using global time synchronization. However, these schemes remain vulnerable to jamming attacks. In this paper, we first analyze the limitations of quorum-based rendezvous schemes called asynchronous channel hopping (ACH. Then, we introduce a novel sequence sensing jamming attack (SSJA model in which a sophisticated jammer can dramatically reduce the rendezvous success rates of ACH schemes. In addition, we propose a fast and robust asynchronous rendezvous scheme (FRARS that can significantly enhance robustness under jamming attacks. Our numerical results demonstrate that the performance of the proposed scheme vastly outperforms the ACH scheme when there are security concerns about a sequence sensing jammer.

Strategic farsighted learning in competitive multi-agent games

NARCIS (Netherlands)

t Hoen, P.J.; Bohté, S.M.; Poutré, la J.A.; Brewka, G.; Coradeschi, S.; Perini, A.

2006-01-01

We describe a generalized Q-learning type algorithm for reinforcement learning in competitive multi-agent games. We make the observation that in a competitive setting with adaptive agents an agent's actions will (likely) result in changes in the opponents policies. In addition to accounting for the

Determining a hopping polaron's bandwidth from its Seebeck coefficient: Measuring the disorder energy of a non-crystalline semiconductor

International Nuclear Information System (INIS)

Emin, David

2016-01-01

Charge carriers that execute multi-phonon hopping generally interact strongly enough with phonons to form polarons. A polaron's sluggish motion is linked to slowly shifting atomic displacements that severely reduce the intrinsic width of its transport band. Here a means to estimate hopping polarons' bandwidths from Seebeck-coefficient measurements is described. The magnitudes of semiconductors' Seebeck coefficients are usually quite large (>k/|q| = 86 μV/K) near room temperature. However, in accord with the third law of thermodynamics, Seebeck coefficients must vanish at absolute zero. Here, the transition of the Seebeck coefficient of hopping polarons to its low-temperature regime is investigated. The temperature and sharpness of this transition depend on the concentration of carriers and on the width of their transport band. This feature provides a means of estimating the width of a polaron's transport band. Since the intrinsic broadening of polaron bands is very small, less than the characteristic phonon energy, the net widths of polaron transport bands in disordered semiconductors approach the energetic disorder experienced by their hopping carriers, their disorder energy

Relationships between Xanthohumol and Polyphenol Content in Hop Leaves and Hop Cones with Regard to Water Supply and Cultivar

Science.gov (United States)

Čeh, Barbara; Kač, Milica; Košir, Iztok J.; Abram, Veronika

2007-01-01

The effect of water supply – especially of drought stress – on the content of some secondary metabolites in hops (Humulus lupulus L.) was studied. The experiment took place in 2006. Some relevant data from 2005 were included for comparison. Leaves and cones of nine hop cultivars grown under field conditions as well as in a pot experiment under three water regimes were analyzed. The cultivars ranged from those most grown in Slovenia to promising crossbreed being tested. Leaves were sampled from July 18, 2006 to August 18, 2006, while cones were picked in the time of technological maturity. Standard analytical methods were applied to determine the contents of xanthohumol, polyphenols and α-acids in hop leaves and hop cones. The contents of the secondary metabolites in question depended more on the cultivar under investigation than on the water supply, at least as far the growing conditions for a relatively normal development of the plant were met.

A two-stage multi-view learning framework based computer-aided diagnosis of liver tumors with contrast enhanced ultrasound images.

Science.gov (United States)

Guo, Le-Hang; Wang, Dan; Qian, Yi-Yi; Zheng, Xiao; Zhao, Chong-Ke; Li, Xiao-Long; Bo, Xiao-Wan; Yue, Wen-Wen; Zhang, Qi; Shi, Jun; Xu, Hui-Xiong

2018-04-04

With the fast development of artificial intelligence techniques, we proposed a novel two-stage multi-view learning framework for the contrast-enhanced ultrasound (CEUS) based computer-aided diagnosis for liver tumors, which adopted only three typical CEUS images selected from the arterial phase, portal venous phase and late phase. In the first stage, the deep canonical correlation analysis (DCCA) was performed on three image pairs between the arterial and portal venous phases, arterial and delayed phases, and portal venous and delayed phases respectively, which then generated total six-view features. While in the second stage, these multi-view features were then fed to a multiple kernel learning (MKL) based classifier to further promote the diagnosis result. Two MKL classification algorithms were evaluated in this MKL-based classification framework. We evaluated proposed DCCA-MKL framework on 93 lesions (47 malignant cancers vs. 46 benign tumors). The proposed DCCA-MKL framework achieved the mean classification accuracy, sensitivity, specificity, Youden index, false positive rate, and false negative rate of 90.41 ± 5.80%, 93.56 ± 5.90%, 86.89 ± 9.38%, 79.44 ± 11.83%, 13.11 ± 9.38% and 6.44 ± 5.90%, respectively, by soft margin MKL classifier. The experimental results indicate that the proposed DCCA-MKL framework achieves best performance for discriminating benign liver tumors from malignant liver cancers. Moreover, it is also proved that the three-phase CEUS image based CAD is feasible for liver tumors with the proposed DCCA-MKL framework.

Robust visual tracking via structured multi-task sparse learning

KAUST Repository

Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra

2012-01-01

In this paper, we formulate object tracking in a particle filter framework as a structured multi-task sparse learning problem, which we denote as Structured Multi-Task Tracking (S-MTT). Since we model particles as linear combinations of dictionary

Toward Hip-Hop Pedagogies for Music Education

Science.gov (United States)

Kruse, Adam J.

2016-01-01

Music education scholarship in the areas of popular, vernacular, and participatory musicianship has grown in the past decades; however, music education research concerned specifically with hip-hop has been relatively scarce. Because hip-hop music can differ tremendously from the traditional western genres with which many music educators are most…

Hip-Hop Guayaquil: culturas viajeras e identidades locales

Directory of Open Access Journals (Sweden)

1999-01-01

Full Text Available HIP-HOP GUAYAQUIL: CULTURES ITINÉRANTES ET IDENTITES LOCALES. Le hip-hop est un style de musique contemporaine caractérisé par une orchestration d’œuvres lyriques rapées, la superposition de morceaux de musique enregistrés dans le passé par différents artistes, et une instrumentation électronique, tout cela sur des rythmes de basse réguliers et constants. Le hip-hop, musique accompagnée de ses propres danses et de sa mode, est le produit du déplacement et de la transformation d’une variété d’idéologies politiques de la communauté noire qui se constituent à partir de relations qui se modifient entre elles, et en relation avec les cultures dominantes contre lesquelles elles luttent quotidiennement. À l’origine, le hip-hop est lié à des mouvements d’identité de jeunes noirs. Dans cet article, il est intéressant d’étudier le rôle du hip-hop dans la formulation d’une identité entre jeunes métisses et noirs des secteurs populaires de Guayaquil. Cet exemple illustre la nécessité d’inclure dans l’analyse les dimensions politiques des processus de traduction du global au niveau local. El hip-hop es un género de música contemporánea caracterizado por la orquestación de líricas que son rapeadas, superposición de fragmentos de música grabada en el pasado por diferentes artistas, e instrumentación electrónica, todo ello sobre ritmos de bajo regulares y constantes. Como un tipo de música acompañado por sus propias formas de danza y moda, el hip-hop es producto del viaje y la transformación de una variedad de ideologías políticas de la comunidad negra que se constituyen a sí mismas en relaciones cambiantes entre sí y en relación a las culturas dominantes contra las cuales luchan cotidianamente. El hip-hop está ligado, en su contexto originario, a políticas de identidad defendidas por jóvenes negros. Lo que interesa explorar en este artículo es el papel del hip-hop en la formulación de una identidad

Vortex variable range hopping in a conventional superconducting film

Science.gov (United States)

Percher, Ilana M.; Volotsenko, Irina; Frydman, Aviad; Shklovskii, Boris I.; Goldman, Allen M.

2017-12-01

The behavior of a disordered amorphous thin film of superconducting indium oxide has been studied as a function of temperature and magnetic field applied perpendicular to its plane. A superconductor-insulator transition has been observed, though the isotherms do not cross at a single point. The curves of resistance versus temperature on the putative superconducting side of this transition, where the resistance decreases with decreasing temperature, obey two-dimensional Mott variable-range hopping of vortices over wide ranges of temperature and resistance. To estimate the parameters of hopping, the film is modeled as a granular system and the hopping of vortices is treated in a manner analogous to hopping of charges. The reason the long-range interaction between vortices over the range of magnetic fields investigated does not lead to a stronger variation of resistance with temperature than that of two-dimensional Mott variable-range hopping remains unresolved.

Collective probabilities algorithm for surface hopping calculations

International Nuclear Information System (INIS)

Bastida, Adolfo; Cruz, Carlos; Zuniga, Jose; Requena, Alberto

2003-01-01

General equations that transition probabilities of the hopping algorithms in surface hopping calculations must obey to assure the equality between the average quantum and classical populations are derived. These equations are solved for two particular cases. In the first it is assumed that probabilities are the same for all trajectories and that the number of hops is kept to a minimum. These assumptions specify the collective probabilities (CP) algorithm, for which the transition probabilities depend on the average populations for all trajectories. In the second case, the probabilities for each trajectory are supposed to be completely independent of the results from the other trajectories. There is, then, a unique solution of the general equations assuring that the transition probabilities are equal to the quantum population of the target state, which is referred to as the independent probabilities (IP) algorithm. The fewest switches (FS) algorithm developed by Tully is accordingly understood as an approximate hopping algorithm which takes elements from the accurate CP and IP solutions. A numerical test of all these hopping algorithms is carried out for a one-dimensional two-state problem with two avoiding crossings which shows the accuracy and computational efficiency of the collective probabilities algorithm proposed, the limitations of the FS algorithm and the similarity between the results offered by the IP algorithm and those obtained with the Ehrenfest method

Tensor-based Multi-view Feature Selection with Applications to Brain Diseases

Science.gov (United States)

Cao, Bokai; He, Lifang; Kong, Xiangnan; Yu, Philip S.; Hao, Zhifeng; Ragin, Ann B.

2015-01-01

In the era of big data, we can easily access information from multiple views which may be obtained from different sources or feature subsets. Generally, different views provide complementary information for learning tasks. Thus, multi-view learning can facilitate the learning process and is prevalent in a wide range of application domains. For example, in medical science, measurements from a series of medical examinations are documented for each subject, including clinical, imaging, immunologic, serologic and cognitive measures which are obtained from multiple sources. Specifically, for brain diagnosis, we can have different quantitative analysis which can be seen as different feature subsets of a subject. It is desirable to combine all these features in an effective way for disease diagnosis. However, some measurements from less relevant medical examinations can introduce irrelevant information which can even be exaggerated after view combinations. Feature selection should therefore be incorporated in the process of multi-view learning. In this paper, we explore tensor product to bring different views together in a joint space, and present a dual method of tensor-based multi-view feature selection (dual-Tmfs) based on the idea of support vector machine recursive feature elimination. Experiments conducted on datasets derived from neurological disorder demonstrate the features selected by our proposed method yield better classification performance and are relevant to disease diagnosis. PMID:25937823

Higher order capacity statistics of multi-hop transmission systems over Rayleigh fading channels

KAUST Repository

Yilmaz, Ferkan

2012-03-01

In this paper, we present an exact analytical expression to evaluate the higher order statistics of the channel capacity for amplify and forward (AF) multihop transmission systems operating over Rayleigh fading channels. Furthermore, we present simple and efficient closed-form expression to the higher order moments of the channel capacity of dual hop transmission system with Rayleigh fading channels. In order to analyze the behavior of the higher order capacity statistics and investigate the usefulness of the mathematical analysis, some selected numerical and simulation results are presented. Our results are found to be in perfect agreement. © 2012 IEEE.

"Folkbildning" through Hip-Hop: How the Ideals of Three Rappers Parallel a Scandinavian Educational Tradition

Science.gov (United States)

Soderman, Johan

2011-01-01

The purpose of this article is to show how the rappers' talk about hip-hop and its connection to pedagogy and social activism parallel the Scandinavian tradition of folkbildning. Scandinavian folkbildning can be seen as a movement to provide voluntary education for the general population. It can also be the name of the process of learning in which…

Subunit Organisation of In Vitro Reconstituted HOPS and CORVET Multisubunit Membrane Tethering Complexes

Science.gov (United States)

Guo, Zhong; Johnston, Wayne; Kovtun, Oleksiy; Mureev, Sergey; Bröcker, Cornelia; Ungermann, Christian; Alexandrov, Kirill

2013-01-01

Biochemical and structural analysis of macromolecular protein assemblies remains challenging due to technical difficulties in recombinant expression, engineering and reconstitution of multisubunit complexes. Here we use a recently developed cell-free protein expression system based on the protozoan Leishmania tarentolae to produce in vitro all six subunits of the 600 kDa HOPS and CORVET membrane tethering complexes. We demonstrate that both subcomplexes and the entire HOPS complex can be reconstituted in vitro resulting in a comprehensive subunit interaction map. To our knowledge this is the largest eukaryotic protein complex in vitro reconstituted to date. Using the truncation and interaction analysis, we demonstrate that the complex is assembled through short hydrophobic sequences located in the C-terminus of the individual Vps subunits. Based on this data we propose a model of the HOPS and CORVET complex assembly that reconciles the available biochemical and structural data. PMID:24312556

Interactive Preference Learning of Utility Functions for Multi-Objective Optimization

OpenAIRE

Dewancker, Ian; McCourt, Michael; Ainsworth, Samuel

2016-01-01

Real-world engineering systems are typically compared and contrasted using multiple metrics. For practical machine learning systems, performance tuning is often more nuanced than minimizing a single expected loss objective, and it may be more realistically discussed as a multi-objective optimization problem. We propose a novel generative model for scalar-valued utility functions to capture human preferences in a multi-objective optimization setting. We also outline an interactive active learn...

Hip-Hop(e): The Cultural Practice and Critical Pedagogy of International Hip-Hop. Adolescent Cultures, School, and Society. Volume 56

Science.gov (United States)

Porfilio, Brad J., Ed.; Viola, Michael J., Ed.

2012-01-01

Illuminating hip-hop as an important cultural practice and a global social movement, this collaborative project highlights the emancipatory messages and cultural work generated by the organic intellectuals of global hip-hop. Contributors describe the social realities--globalization, migration, poverty, criminalization, and racism--youth are…

Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods.

Science.gov (United States)

Zhang, Wen; Zhu, Xiaopeng; Fu, Yu; Tsuji, Junko; Weng, Zhiping

2017-12-01

Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human splicing branchpoints, but many branchpoints are still unknown. In order to guide wet experiments, we develop computational methods to predict human splicing branchpoints. Considering the fact that an intron may have multiple branchpoints, we transform the branchpoint prediction as the multi-label learning problem, and attempt to predict branchpoint sites from intron sequences. First, we investigate a variety of intron sequence-derived features, such as sparse profile, dinucleotide profile, position weight matrix profile, Markov motif profile and polypyrimidine tract profile. Second, we consider several multi-label learning methods: partial least squares regression, canonical correlation analysis and regularized canonical correlation analysis, and use them as the basic classification engines. Third, we propose two ensemble learning schemes which integrate different features and different classifiers to build ensemble learning systems for the branchpoint prediction. One is the genetic algorithm-based weighted average ensemble method; the other is the logistic regression-based ensemble method. In the computational experiments, two ensemble learning methods outperform benchmark branchpoint prediction methods, and can produce high-accuracy results on the benchmark dataset.

Structure and Charge Hopping Dynamics in Green Rust

International Nuclear Information System (INIS)

Wander, Matthew C.; Rosso, Kevin M.; Schoonen, Martin A.

2007-01-01

Green rust is a family of mixed-valent iron phases formed by a number of abiotic and biotic processes under alkaline suboxic conditions. Due to its high Fe2+ content, green rust is a potentially important phase for pollution remediation by serving as a powerful electron donor for reductive transformation. However, mechanisms of oxidation of this material are poorly understood. An essential component of the green rust structure is a mixed-valent brucite-like Fe(OH)2 sheet comprised of a two dimensional network of edge-sharing iron octahedra. Room temperature Mossbauer spectra show a characteristic signature for intermediate valence on the iron atoms in this sheet, indicative of a Fe2+-Fe3+ valence interchange reaction faster than approximately 107s-1. Using Fe(OH)2 as structural analogue for reduced green rust, we performed Hartree-Fock calculations on periodic slab models and cluster representations to determine the structure and hopping mobility of Fe3+ hole polarons in this material, providing a first principles assessment of the Fe2+-Fe3+ valence interchange reaction rate. The calculations show that among three possible symmetry unique iron-to-iron hops within a sheet, a hop to next-nearest neighbors at an intermediate distance of 5.6Angstroms is the fastest. The predicted rate is on the order of 1012 s-1 consistent the Mossbauer-based constraint. All other possibilities, including hopping across interlayer spaces, are predicted to be slower than 107s-1. Collectively, the findings suggest the possibility of hole self-diffusion along sheets as a mechanism for regeneration of lattice Fe2+ sites, consistent with previous experimental observations of edge-inward progressive oxidation of green rust.

Assessing hopping developmental level in childhood using wearable inertial sensor devices.

Science.gov (United States)

Masci, Ilaria; Vannozzi, Giuseppe; Getchell, Nancy; Cappozzo, Aurelio

2012-07-01

Assessing movement skills is a fundamental issue in motor development. Current process-oriented assessments, such as developmental sequences, are based on subjective judgments; if paired with quantitative assessments, a better understanding of movement performance and developmental change could be obtained. Our purpose was to examine the use of inertial sensors to evaluate developmental differences in hopping over distance. Forty children executed the task wearing the inertial sensor and relevant time durations and 3D accelerations were obtained. Subjects were also categorized in different developmental levels according to the hopping developmental sequence. Results indicated that some time and kinematic parameters changed with some developmental levels, possibly as a function of anthropometry and previous motor experience. We concluded that, since inertial sensors were suitable in describing hopping performance and sensitive to developmental changes, this technology is promising as an in-field and user-independent motor development assessment tool.

Transferring an educational board game to a multi-user mobile learning game to increase shared situational awareness

NARCIS (Netherlands)

Klemke, Roland; Kurapati, Shalini; Kolfschoten, Gwendolyn

2013-01-01

Klemke, R., Kurapati, S., & Kolfschoten, G. (2013, 6 June). Transferring an educational board game to a multi-user mobile learning game to increase shared situational awareness. Presentation at the 3rd Irish Symposium on Game Based Learning, Dublin, Ireland. Please see also

An efficient solution to the decoherence enhanced trivial crossing problem in surface hopping

Science.gov (United States)

Bai, Xin; Qiu, Jing; Wang, Linjun

2018-03-01

We provide an in-depth investigation of the time interval convergence when both trivial crossing and decoherence corrections are applied to Tully's fewest switches surface hopping (FSSH) algorithm. Using one force-based and one energy-based decoherence strategies as examples, we show decoherence corrections intrinsically enhance the trivial crossing problem. We propose a restricted decoherence (RD) strategy and incorporate it into the self-consistent (SC) fewest switches surface hopping algorithm [L. Wang and O. V. Prezhdo, J. Phys. Chem. Lett. 5, 713 (2014)]. The resulting SC-FSSH-RD approach is applied to general Hamiltonians with different electronic couplings and electron-phonon couplings to mimic charge transport in tens to hundreds of molecules. In all cases, SC-FSSH-RD allows us to use a large time interval of 0.1 fs for convergence and the simulation time is reduced by over one order of magnitude. Both the band and hopping mechanisms of charge transport have been captured perfectly. SC-FSSH-RD makes surface hops in the adiabatic representation and can be implemented in both diabatic and locally diabatic representations for wave function propagation. SC-FSSH-RD can potentially describe general nonadiabatic dynamics of electrons and excitons in organics and other materials.

The Hip-Hop club scene: Gender, grinding and sex.

Science.gov (United States)

Muñoz-Laboy, Miguel; Weinstein, Hannah; Parker, Richard

2007-01-01

Hip-Hop culture is a key social medium through which many young men and women from communities of colour in the USA construct their gender. In this study, we focused on the Hip-Hop club scene in New York City with the intention of unpacking narratives of gender dynamics from the perspective of young men and women, and how these relate to their sexual experiences. We conducted a three-year ethnographic study that included ethnographic observations of Hip-Hop clubs and their social scene, and in-depth interviews with young men and young women aged 15-21. This paper describes how young people negotiate gender relations on the dance floor of Hip-Hop clubs. The Hip-Hop club scene represents a context or setting where young men's masculinities are contested by the social environment, where women challenge hypermasculine privilege and where young people can set the stage for what happens next in their sexual and emotional interactions. Hip-Hop culture therefore provides a window into the gender and sexual scripts of many urban minority youth. A fuller understanding of these patterns can offer key insights into the social construction of sexual risk, as well as the possibilities for sexual health promotion, among young people in urban minority populations.

Multi-mode energy management strategy for fuel cell electric vehicles based on driving pattern identification using learning vector quantization neural network algorithm

Science.gov (United States)

Song, Ke; Li, Feiqiang; Hu, Xiao; He, Lin; Niu, Wenxu; Lu, Sihao; Zhang, Tong

2018-06-01

The development of fuel cell electric vehicles can to a certain extent alleviate worldwide energy and environmental issues. While a single energy management strategy cannot meet the complex road conditions of an actual vehicle, this article proposes a multi-mode energy management strategy for electric vehicles with a fuel cell range extender based on driving condition recognition technology, which contains a patterns recognizer and a multi-mode energy management controller. This paper introduces a learning vector quantization (LVQ) neural network to design the driving patterns recognizer according to a vehicle's driving information. This multi-mode strategy can automatically switch to the genetic algorithm optimized thermostat strategy under specific driving conditions in the light of the differences in condition recognition results. Simulation experiments were carried out based on the model's validity verification using a dynamometer test bench. Simulation results show that the proposed strategy can obtain better economic performance than the single-mode thermostat strategy under dynamic driving conditions.

Hybrid Augmented Reality for Participatory Learning: The Hidden Efficacy of Multi-User Game-Based Simulation

Science.gov (United States)

Oh, Seungjae; So, Hyo-Jeong; Gaydos, Matthew

2018-01-01

The goal for this research is to articulate and test a new hybrid Augmented Reality (AR) environment for conceptual understanding. From the theoretical lens of embodied interaction, we have designed a multi-user participatory simulation called ARfract where visitors in a science museum can learn about complex scientific concepts on the refraction…

Design, testing, and performance of a hybrid micro vehicle---The Hopping Rotochute

Science.gov (United States)

Beyer, Eric W.

The Hopping Rotochute is a new hybrid micro vehicle that has been developed to robustly explore environments with rough terrain while minimizing energy consumption over long periods of time. The device consists of a small coaxial rotor system housed inside a lightweight cage. The vehicle traverses an area by intermittently powering a small electric motor which drives the rotor system, allowing the vehicle to hop over obstacles of various shapes and sizes. A movable internal mass controls the direction of travel while the egg-like exterior shape and low mass center allows the vehicle to passively reorient itself to an upright attitude when in contact with the ground. This dissertation presents the design, fabrication, and testing of a radio-controlled Hopping Rotochute prototype as well as an analytical study of the flight performance of the device. The conceptual design iterations are first outlined which were driven by the mission and system requirements assigned to the vehicle. The aerodynamic, mechanical, and electrical design of a prototype is then described, based on the final conceptual design, with particular emphasis on the fundamental trades that must be negotiated for this type of hopping vehicle. The fabrication and testing of this prototype is detailed as well as experimental results obtained from a motion capture system. Basic flight performance of the prototype are reported which demonstrates that the Hopping Rotochute satisfies all appointed system requirements. A dynamic model of the Hopping Rotochute is also developed in this thesis and employed to predict the flight performance of the vehicle. The dynamic model includes aerodynamic loads from the body and rotor system as well as a soft contact model to estimate the forces and moments during ground contact. The experimental methods used to estimate the dynamic model parameters are described while comparisons between measured and simulated motion are presented. Good correlation between these motions

ARLearn and StreetLearn software for virtual reality and augmented reality multi user learning games

NARCIS (Netherlands)

Ternier, Stefaan; Klemke, Roland

2012-01-01

Ternier, S., & Klemke, R. (2011). ARLearn and StreetLearn software for virtual reality and augmented reality multi user learning games (Version 1.0) [Software Documentation]. Heerlen, The Netherlands: Open Universiteit in the Netherlands.

ARLearn and StreetLearn software for virtual reality and augmented reality multi user learning games

NARCIS (Netherlands)

Ternier, Stefaan; Klemke, Roland

2012-01-01

Ternier, S., & Klemke, R. (2011). ARLearn and StreetLearn software for virtual reality and augmented reality multi user learning games (Version 1.0) [Computer software]. Heerlen, The Netherlands: Open Universiteit in the Netherlands.

Reinforcement Learning Based on the Bayesian Theorem for Electricity Markets Decision Support

DEFF Research Database (Denmark)

Sousa, Tiago; Pinto, Tiago; Praca, Isabel

2014-01-01

This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi...

Hip hop jako kulturní styl, jeho spicifika a vliv na teenagery

OpenAIRE

POSPÍŠIL, Jan

2008-01-01

This thesis involves history of hip hop, its specifics and elements, it talks about influence of hip hip subculture on teenagers and points to positive and negative aspects connected to this culture style. In this way is work sectionalized into chapters. First part talks about history of hip hop, connection between religion and hip hop and also about Czech hip hop. Second part specifies on main elements of hip hop culture as DJing, MCing, breakdance, beatbox and graffiti. Last part focuses on...

Switched diversity strategies for dual-hop amplify-and-forward relaying systems

KAUST Repository

Gaaloul, Fakhreddine

2012-01-01

This study investigates different receive single-branch switch-based diversity schemes for dual-hop amplify-and-forward relaying networks. Specifically, three receive processing algorithms are adopted, in which the receive branch is selected using the arbitrary selection algorithm, the switching algorithm, or the switching algorithm with post-examining best branch selection. The identification of the receive branch is carried out for two different system models. For the first model, a single-antenna relaying station is used in conjunction with a multiple-antenna transceiver, where the processing is performed independently of the first hop-fading conditions. The second model suggests the use of parallel deployment of single-antenna relays to transfer information from a multiple-antenna transmitter to a single-antenna receiver, where the active relaying station is determined based on the pre-combining end-to-end fading conditions. Performance comparisons for various transmission scenarios on the first hop are presented using new formulations for the statistics of the combined signal-to-noise ratio. Simulation results are also provided to validate the mathematical development and to verify the numerical computations. © 2012 The Institution of Engineering and Technology.

The content of vitamine E in hop cones of the Saaz variety

Directory of Open Access Journals (Sweden)

Helena Pluháčková

2013-01-01

Full Text Available The activity of vitamin E, total content of tocols and the content of individual isomers: α-tocopherols, β-tocopherols, γ-tocopherols and δ-tocopherols was monitored in samples of hop cones of the world-important Saaz variety. Hop cone samples originated from hop-breeding area Tršice, Czech Republic. The method used for the determination of vitamin E in barley was modified and used for this quantitative analysis. The results indicate that monitored characteristics are influenced by the year of harvest (2010 or 2011 but also by the age of hop-gardens (hop bucks. High values of vitamin E activity (up to 67.79 mg.kg−1 and total content of tocols (up to 76.31 mg.kg−1 in hop cones are worth further attention from the viewpoint of alternative use of hops.

Mode competition and hopping in optomechanical nano-oscillators

Science.gov (United States)

Zhang, Xingwang; Lin, Tong; Tian, Feng; Du, Han; Zou, Yongchao; Chau, Fook Siong; Zhou, Guangya

2018-04-01

We investigate the inter-mode nonlinear interaction in the multi-mode optomechanical nano-oscillator which consists of coupled silicon nanocantilevers, where the integrated photonic crystal nanocavities provide the coupling between the optical and mechanical modes. Due to the self-saturation and cross-saturation of the mechanical gain, the inter-mode competition is observed, which leads to the bistable operation of the optomechanical nano-oscillator: only one of the mechanical modes can oscillate at any one time, and the oscillation of one mode extremely suppresses that of the other with a side mode suppression ratio (SMSR) up to 40 dB. In the meantime, mode hopping, i.e., the optomechanical oscillation switches from one mode to the other, is also observed and found to be able to be provoked by excitation laser fluctuations.

Romani Music - Roma and the Hip-hop Culture

OpenAIRE

Dočkal, Tomáš

2007-01-01

This thesis is focused on Romani music and its importance for the Romani culture. It examines the popularity of hip-hop among the young Romani generation and Romani hip- hip production. It attempts to define the role of hip-hop culture in young Romanies' lives.

Multi-representation based on scientific investigation for enhancing students’ representation skills

Science.gov (United States)

Siswanto, J.; Susantini, E.; Jatmiko, B.

2018-03-01

This research aims to implementation learning physics with multi-representation based on the scientific investigation for enhancing students’ representation skills, especially on the magnetic field subject. The research design is one group pretest-posttest. This research was conducted in the department of mathematics education, Universitas PGRI Semarang, with the sample is students of class 2F who take basic physics courses. The data were obtained by representation skills test and documentation of multi-representation worksheet. The Results show gain analysis value of .64 which means some medium improvements. The result of t-test (α = .05) is shows p-value = .001. This learning significantly improves students representation skills.

Being Hip-Hop: Beyond Skills and Songs

Science.gov (United States)

Kruse, Adam J.

2016-01-01

In this article, I offer four principles relevant to hip-hop cultures (keep it real, flip the script, make some noise, and stay fresh) and explore how these principles might affect music classrooms. I argue that a music classroom that works to keep it real, flip the script, make some noise, and stay fresh might go beyond teaching hip-hop skills…

Escola e movimento hip hop: o campo das possibilidades educativas para a juventude / Education and the hip hop movement: the field of educative possibilities for the youth

Directory of Open Access Journals (Sweden)

Jaileila de Araújo Menezes

2010-09-01

citizenship, political culture, the configuration of sociopolitical and economic scenario, of subjectivity and political organization. For this we follow a crew activities developed in the movement located in an outlying neighborhood of the city and educational practice that movement in the school limited the Open School Program. Visualize the experience of hip hop movement in the program a learning opportunity for the school in order to contextualize their knowledge in order to gain greater compliance of the school community, especially young people. Accordingly, we find two types of ownership of the educational practices of the movement for school: teaching and instrumental, which signal the need for integration of the Program in educational policy and educational policy projects. With follow-up activities and meetings we discuss the interface education / safety program at this as a limiting factor for the learning of participation expected for the school in a democratic context. We demonstrated this in hip hop workshops where young people with the task of educating other young people faced with this dilemma or simply succumb to a policy which unpowered their educational practices.

Basin Hopping Graph

DEFF Research Database (Denmark)

Kucharik, Marcel; Hofacker, Ivo; Stadler, Peter

2014-01-01

of the folding free energy landscape, however, can provide the relevant information. Results We introduce the basin hopping graph (BHG) as a novel coarse-grained model of folding landscapes. Each vertex of the BHG is a local minimum, which represents the corresponding basin in the landscape. Its edges connect...

Position-aware deep multi-task learning for drug-drug interaction extraction.

Science.gov (United States)

Zhou, Deyu; Miao, Lei; He, Yulan

2018-05-01

A drug-drug interaction (DDI) is a situation in which a drug affects the activity of another drug synergistically or antagonistically when being administered together. The information of DDIs is crucial for healthcare professionals to prevent adverse drug events. Although some known DDIs can be found in purposely-built databases such as DrugBank, most information is still buried in scientific publications. Therefore, automatically extracting DDIs from biomedical texts is sorely needed. In this paper, we propose a novel position-aware deep multi-task learning approach for extracting DDIs from biomedical texts. In particular, sentences are represented as a sequence of word embeddings and position embeddings. An attention-based bidirectional long short-term memory (BiLSTM) network is used to encode each sentence. The relative position information of words with the target drugs in text is combined with the hidden states of BiLSTM to generate the position-aware attention weights. Moreover, the tasks of predicting whether or not two drugs interact with each other and further distinguishing the types of interactions are learned jointly in multi-task learning framework. The proposed approach has been evaluated on the DDIExtraction challenge 2013 corpus and the results show that with the position-aware attention only, our proposed approach outperforms the state-of-the-art method by 0.99% for binary DDI classification, and with both position-aware attention and multi-task learning, our approach achieves a micro F-score of 72.99% on interaction type identification, outperforming the state-of-the-art approach by 1.51%, which demonstrates the effectiveness of the proposed approach. Copyright © 2018 Elsevier B.V. All rights reserved.

Rapid differentiation of Chinese hop varieties (Humulus lupulus) using volatile fingerprinting by HS-SPME-GC-MS combined with multivariate statistical analysis.

Science.gov (United States)

Liu, Zechang; Wang, Liping; Liu, Yumei

2018-01-18

Hops impart flavor to beer, with the volatile components characterizing the various hop varieties and qualities. Fingerprinting, especially flavor fingerprinting, is often used to identify 'flavor products' because inconsistencies in the description of flavor may lead to an incorrect definition of beer quality. Compared to flavor fingerprinting, volatile fingerprinting is simpler and easier. We performed volatile fingerprinting using head space-solid phase micro-extraction gas chromatography-mass spectrometry combined with similarity analysis and principal component analysis (PCA) for evaluating and distinguishing between three major Chinese hops. Eighty-four volatiles were identified, which were classified into seven categories. Volatile fingerprinting based on similarity analysis did not yield any obvious result. By contrast, hop varieties and qualities were identified using volatile fingerprinting based on PCA. The potential variables explained the variance in the three hop varieties. In addition, the dendrogram and principal component score plot described the differences and classifications of hops. Volatile fingerprinting plus multivariate statistical analysis can rapidly differentiate between the different varieties and qualities of the three major Chinese hops. Furthermore, this method can be used as a reference in other fields. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Hip Hop Culture's OGs: A Narrative Inquiry into the Intersection of Hip Hop Culture, Black Males and Their Schooling Experiences

Science.gov (United States)

Buchanan, Ian P.

2013-01-01

Using a critical race lens, this narrative study employs a focus group design to explore the intersections between black males, hip hop culture and schooling experiences. To provide a sociocultural grounding, this study first reviews the research literature around hip hop culture.s sociocultural development and its impact as a culture force that…

On a Hopping-Points SVD and Hough Transform-Based Line Detection Algorithm for Robot Localization and Mapping

Directory of Open Access Journals (Sweden)

Abhijeet Ravankar

2016-05-01

Full Text Available Line detection is an important problem in computer vision, graphics and autonomous robot navigation. Lines detected using a laser range sensor (LRS mounted on a robot can be used as features to build a map of the environment, and later to localize the robot in the map, in a process known as Simultaneous Localization and Mapping (SLAM. We propose an efficient algorithm for line detection from LRS data using a novel hopping-points Singular Value Decomposition (SVD and Hough transform-based algorithm, in which SVD is applied to intermittent LRS points to accelerate the algorithm. A reverse-hop mechanism ensures that the end points of the line segments are accurately extracted. Line segments extracted from the proposed algorithm are used to form a map and, subsequently, LRS data points are matched with the line segments to localize the robot. The proposed algorithm eliminates the drawbacks of point-based matching algorithms like the Iterative Closest Points (ICP algorithm, the performance of which degrades with an increasing number of points. We tested the proposed algorithm for mapping and localization in both simulated and real environments, and found it to detect lines accurately and build maps with good self-localization.

Multi-documents summarization based on clustering of learning object using hierarchical clustering

Science.gov (United States)

Mustamiin, M.; Budi, I.; Santoso, H. B.

2018-03-01

The Open Educational Resources (OER) is a portal of teaching, learning and research resources that is available in public domain and freely accessible. Learning contents or Learning Objects (LO) are granular and can be reused for constructing new learning materials. LO ontology-based searching techniques can be used to search for LO in the Indonesia OER. In this research, LO from search results are used as an ingredient to create new learning materials according to the topic searched by users. Summarizing-based grouping of LO use Hierarchical Agglomerative Clustering (HAC) with the dependency context to the user’s query which has an average value F-Measure of 0.487, while summarizing by K-Means F-Measure only has an average value of 0.336.

Vulnerability And Risk Assessment Using The Homeland-Defense Operational Planning System (HOPS)

International Nuclear Information System (INIS)

Durling, R.L. Jr.; Price, D.E.; Spero, K.K.

2005-01-01

For over ten years, the Counterproliferation Analysis and Planning System (CAPS) at Lawrence Livermore National Laboratory (LLNL) has been a planning tool used by U.S. combatant commands for mission support planning against foreign programs engaged in the manufacture of weapons of mass destruction (WMD). CAPS is endorsed by the Secretary of Defense as the preferred counterproliferation tool to be used by the nation's armed services. A sister system, the Homeland-Defense Operational Planning System (HOPS), is a new operational planning tool leveraging CAPS expertise designed to support the defense of the U.S. homeland. HOPS provides planners with a basis to make decisions to protect against acts of terrorism, focusing on the defense of facilities critical to U.S. infrastructure. Criticality of facilities, structures, and systems is evaluated on a composite matrix of specific projected casualty, economic, and sociopolitical impact bins. Based on these criteria, significant unidentified vulnerabilities are identified and secured. To provide insight into potential successes by malevolent actors, HOPS analysts strive to base their efforts mainly on unclassified open-source data. However, more cooperation is needed between HOPS analysts and facility representatives to provide an advantage to those whose task is to defend these facilities. Evaluated facilities include: refineries, major ports, nuclear power plants and other nuclear licensees, dams, government installations, convention centers, sports stadiums, tourist venues, and public and freight transportation systems. A generalized summary of analyses of U.S. infrastructure facilities is presented

Enhancing the Teaching of Introductory Economics with a Team-Based, Multi-Section Competition

Science.gov (United States)

Beaudin, Laura; Berdiev, Aziz N.; Kaminaga, Allison Shwachman; Mirmirani, Sam; Tebaldi, Edinaldo

2017-01-01

The authors describe a unique approach to enhancing student learning at the introductory economics level that utilizes a multi-section, team-based competition. The competition is structured to supplement learning throughout the entire introductory course. Student teams are presented with current economic issues, trends, or events, and use economic…

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

Science.gov (United States)

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

L1-norm locally linear representation regularization multi-source adaptation learning.

Science.gov (United States)

Tao, Jianwen; Wen, Shiting; Hu, Wenjun

2015-09-01

In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the established frameworks in existing model-based DAL methods for function learning by incorporating additional information about the target geometric structure of the marginal distribution. We would like to ensure that the solution is smooth with respect to both the ambient space and the target marginal distribution. In doing this, we propose a novel L1-norm locally linear representation regularization multi-source adaptation learning framework which exploits the geometry of the probability distribution, which has two techniques. Firstly, an L1-norm locally linear representation method is presented for robust graph construction by replacing the L2-norm reconstruction measure in LLE with L1-norm one, which is termed as L1-LLR for short. Secondly, considering the robust graph regularization, we replace traditional graph Laplacian regularization with our new L1-LLR graph Laplacian regularization and therefore construct new graph-based semi-supervised learning framework with multi-source adaptation constraint, which is coined as L1-MSAL method. Moreover, to deal with the nonlinear learning problem, we also generalize the L1-MSAL method by mapping the input data points from the input space to a high-dimensional reproducing kernel Hilbert space (RKHS) via a nonlinear mapping. Promising experimental results have been obtained on several real-world datasets such as face, visual video and object. Copyright © 2015 Elsevier Ltd. All rights reserved.

Energy management that generates terrain following versus apex-preserving hopping in man and machine.

Science.gov (United States)

Kalveram, Karl Theodor; Haeufle, Daniel F B; Seyfarth, André; Grimmer, Sten

2012-01-01

While hopping, 12 subjects experienced a sudden step down of 5 or 10 cm. Results revealed that the hopping style was "terrain following". It means that the subjects pursued to keep the distance between maximum hopping height (apex) and ground profile constant. The spring-loaded inverse pendulum (SLIP) model, however, which is currently considered as template for stable legged locomotion would predict apex-preserving hopping, by which the absolute maximal hopping height is kept constant regardless of changes of the ground level. To get more insight into the physics of hopping, we outlined two concepts of energy management: "constant energy supply", by which in each bounce--regardless of perturbations--the same amount of mechanical energy is injected, and "lost energy supply", by which the mechanical energy that is going to be dissipated in the current cycle is assessed and replenished. When tested by simulations and on a robot testbed capable of hopping, constant energy supply generated stable and robust terrain following hopping, whereas lost energy supply led to something like apex-preserving hopping, which, however, lacks stability as well as robustness. Comparing simulated and machine hopping with human hopping suggests that constant energy supply has a good chance to be used by humans to generate hopping.

Transferring an educational board game to a multi-user mobile learning game to increase shared situational awareness

NARCIS (Netherlands)

Klemke, Roland; Kurapati, Shalini; Kolfschoten, Gwendolyn

2013-01-01

Klemke, R., Kurapati, S., & Kolfschoten, G. (2013, 6 June). Transferring an educational board game to a multi-user mobile learning game to increase shared situational awareness. In P. Rooney (Ed.), Proceedings of the 3rd Irish Symposium on Game Based Learning (pp. 8-9). Dublin, Ireland. Please see

Multi-Touch Tables and Collaborative Learning

Science.gov (United States)

Higgins, Steve; Mercier, Emma; Burd, Liz; Joyce-Gibbons, Andrew

2012-01-01

The development of multi-touch tables, an emerging technology for classroom learning, offers valuable opportunities to explore how its features can be designed to support effective collaboration in schools. In this study, small groups of 10- to 11-year-old children undertook a history task where they had to connect various pieces of information…

Flipping the Misogynist Script: Gender, Agency, Hip Hop and Music Education

Science.gov (United States)

Tobias, Evan S.

2014-01-01

Excluding Hip Hop culture and rap music from music education misses opportunities for addressing key aspects of popular culture, society, and students' lives. This article addresses intersections of Hip Hop, gender, and music education to forward potential Hip Hop praxis. After tracing related scholarship, I discuss and problematize…

Hip Hop Dance Experience Linked to Sociocognitive Ability.

Science.gov (United States)

Bonny, Justin W; Lindberg, Jenna C; Pacampara, Marc C

2017-01-01

Expertise within gaming (e.g., chess, video games) and kinesthetic (e.g., sports, classical dance) activities has been found to be linked with specific cognitive skills. Some of these skills, working memory, mental rotation, problem solving, are linked to higher performance in science, technology, math, and engineering (STEM) disciplines. In the present study, we examined whether experience in a different activity, hip hop dance, is also linked to cognitive abilities connected with STEM skills as well as social cognition ability. Dancers who varied in hip hop and other dance style experience were presented with a set of computerized tasks that assessed working memory capacity, mental rotation speed, problem solving efficiency, and theory of mind. We found that, when controlling for demographic factors and other dance style experience, those with greater hip hop dance experience were faster at mentally rotating images of hands at greater angle disparities and there was a trend for greater accuracy at identifying positive emotions displayed by cropped images of human faces. We suggest that hip hop dance, similar to other more technical activities such as video gameplay, tap some specific cognitive abilities that underlie STEM skills. Furthermore, we suggest that hip hop dance experience can be used to reach populations who may not otherwise be interested in other kinesthetic or gaming activities and potentially enhance select sociocognitive skills.

Particle trapping and hopping in an optofluidic fishnet

Science.gov (United States)

Shi, Y. Z.; Xiong, S.; Zhang, Y.; Chin, L. K.; Wu, J. H.; Chen, T. N.; Liu, A. Q.

2017-08-01

Particle jumping between optical potentials has attracted much attention owing to its extensive involvement in many physical and biological experiments. In some circumstances, particle jumping indicates escaping from the optical trap, which is an issue people are trying to avoid. Nevertheless, particle jumping can facilitate the individual trap in each laser spot in the optical lattice and enable sorting and delivery of nanoparticles. Particle hopping has not been seen in fluid because Fluidic drag force dramatically reduce the dwell time of particle or break the potential well. Here, we observe particle hopping in the microchannel by three reasons, e.g., particle collision or aggregation, light disturbing by pretrapped particle and fake trapping position. We show that commonly ignored particle influence to the light could create a new isolated trapping position, where particle hops to the adjacent potential well. The hopping happens in an optofluidic fishnet which is comprised of discrete hotspots enabling 2D patterning of particles in the flow stream for the first time. We also achieve a 2D patterning of cryptosporidium in the microchannel. Our observed particle hopping in the flow stream completes the family of particle kinetics in potential wells and inspires new interests in the particle disturbed optical trapping. The 2D patterning of particles benefits the parallel study of biological samples in the flow stream and have potential on cell sorting and drug delivery.

Hip Hop Dance Experience Linked to Sociocognitive Ability.

Directory of Open Access Journals (Sweden)

Justin W Bonny

Full Text Available Expertise within gaming (e.g., chess, video games and kinesthetic (e.g., sports, classical dance activities has been found to be linked with specific cognitive skills. Some of these skills, working memory, mental rotation, problem solving, are linked to higher performance in science, technology, math, and engineering (STEM disciplines. In the present study, we examined whether experience in a different activity, hip hop dance, is also linked to cognitive abilities connected with STEM skills as well as social cognition ability. Dancers who varied in hip hop and other dance style experience were presented with a set of computerized tasks that assessed working memory capacity, mental rotation speed, problem solving efficiency, and theory of mind. We found that, when controlling for demographic factors and other dance style experience, those with greater hip hop dance experience were faster at mentally rotating images of hands at greater angle disparities and there was a trend for greater accuracy at identifying positive emotions displayed by cropped images of human faces. We suggest that hip hop dance, similar to other more technical activities such as video gameplay, tap some specific cognitive abilities that underlie STEM skills. Furthermore, we suggest that hip hop dance experience can be used to reach populations who may not otherwise be interested in other kinesthetic or gaming activities and potentially enhance select sociocognitive skills.

A Cognitive Skill Classification Based on Multi Objective Optimization Using Learning Vector Quantization for Serious Games

Directory of Open Access Journals (Sweden)

Moh. Aries Syufagi

2013-09-01

Full Text Available Nowadays, serious games and game technology are poised to transform the way of educating and training students at all levels. However, pedagogical value in games do not help novice students learn, too many memorizing and reduce learning process due to no information of player’s ability. To asses the cognitive level of player ability, we propose a Cognitive Skill Game (CSG. CSG improves this cognitive concept to monitor how players interact with the game. This game employs Learning Vector Quantization (LVQ for optimizing the cognitive skill input classification of the player. CSG is using teacher’s data to obtain the neuron vector of cognitive skill pattern supervise. Three clusters multi objective XE "multi objective"  target will be classified as; trial and error, carefully and, expert cognitive skill. In the game play experiments employ 33 respondent players demonstrates that 61% of players have high trial and error, 21% have high carefully, and 18% have high expert cognitive skill. CSG may provide information to game engine when a player needs help or when wanting a formidable challenge. The game engine will provide the appropriate tasks according to players’ ability. CSG will help balance the emotions of players, so players do not get bored and frustrated. 

SDN-based path hopping communication against eavesdropping attack

Science.gov (United States)

Zhang, Chuanhao; Bu, Youjun; Zhao, Zheng

2016-10-01

Network eavesdropping is one of the most popular means used by cyber attackers, which has been a severe threat to network communication security. Adversaries could capture and analyze network communication data from network nodes or links, monitor network status and steal sensitive data such as username and password etc. Traditional network usually uses static network configuration, and existing defense methods, including firewall, IDS, IPS etc., cannot prevent eavesdropping, which has no distinguishing characteristic. Network eavesdropping become silent during most of the time of the attacking process, which is why it is difficult to discover and to defend. But A successful eavesdropping attack also has its' precondition, which is the target path should be relatively stable and has enough time of duration. So, In order to resolve this problem, it has to work on the network architecture. In this paper, a path hopping communication(PHC) mechanism based on Software Define Network (SDN) was proposed to solve this problem. In PHC, Ends in communication packets as well as the routing paths were changed dynamically. Therefore, the traffic would be distributed to multiple flows and transmitted along different paths. so that Network eavesdropping attack could be prevented effectively. It was concluded that PHC was able to increase the overhead of Network eavesdropping, as well as the difficulty of communication data recovery.

Robust segmentation of medical images using competitive hop field neural network as a clustering tool

International Nuclear Information System (INIS)

Golparvar Roozbahani, R.; Ghassemian, M. H.; Sharafat, A. R.

2001-01-01

This paper presents the application of competitive Hop field neural network for medical images segmentation. Our proposed approach consists of Two steps: 1) translating segmentation of the given medical image into an optimization problem, and 2) solving this problem by a version of Hop field network known as competitive Hop field neural network. Segmentation is considered as a clustering problem and its validity criterion is based on both intra set distance and inter set distance. The algorithm proposed in this paper is based on gray level features only. This leads to near optimal solutions if both intra set distance and inter set distance are considered at the same time. If only one of these distances is considered, the result of segmentation process by competitive Hop field neural network will be far from optimal solution and incorrect even for very simple cases. Furthermore, sometimes the algorithm receives at unacceptable states. Both these problems may be solved by contributing both in tera distance and inter distances in the segmentation (optimization) process. The performance of the proposed algorithm is tested on both phantom and real medical images. The promising results and the robustness of algorithm to system noises show near optimal solutions

Droppin’ Knowledge on Race: Hip-Hop, White Adolescents, and Anti-Racism Education

Directory of Open Access Journals (Sweden)

Steven Netcoh

2013-10-01

Full Text Available In this essay, the author examines how Hip-Hop can be mobilized in anti-racism educational initatives.  The author claims that existing research on Hip-Hop and white adolescents suggests a negative corrleation between white youths' engagement with Hip-Hop and their understanding of how race and racism function in American society.  In response to this research, the author argues Hip-Hop's diverse racial discourses and ideologies must be made the subject of direct and critical inquiry in secondary and post-secondary classrooms to maximize its democratic potential.  The author outlines specific approaches for how teachers can employ Hip-Hop in anti-racism curricula in secondary and post-secondary classrooms.  Collectively, the essay serves as a preliminary investigation of Hip-Hop pedagogies of race and whiteness.

Robust visual tracking via multi-task sparse learning

KAUST Repository

Zhang, Tianzhu

2012-06-01

In this paper, we formulate object tracking in a particle filter framework as a multi-task sparse learning problem, which we denote as Multi-Task Tracking (MTT). Since we model particles as linear combinations of dictionary templates that are updated dynamically, learning the representation of each particle is considered a single task in MTT. By employing popular sparsity-inducing p, q mixed norms (p D; 1), we regularize the representation problem to enforce joint sparsity and learn the particle representations together. As compared to previous methods that handle particles independently, our results demonstrate that mining the interdependencies between particles improves tracking performance and overall computational complexity. Interestingly, we show that the popular L 1 tracker [15] is a special case of our MTT formulation (denoted as the L 11 tracker) when p q 1. The learning problem can be efficiently solved using an Accelerated Proximal Gradient (APG) method that yields a sequence of closed form updates. As such, MTT is computationally attractive. We test our proposed approach on challenging sequences involving heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that MTT methods consistently outperform state-of-the-art trackers. © 2012 IEEE.

Exploring Effects of Multi-Touch Tabletop on Collaborative Fraction Learning and the Relationship of Learning Behavior and Interaction with Learning Achievement

Science.gov (United States)

Hwang, Wu-Yuin; Shadiev, Rustam; Tseng, Chi-Wei; Huang, Yueh-Min

2015-01-01

This study designed a learning system to facilitate elementary school students' fraction learning. An experiment was carried out to investigate how the system, which runs on multi-touch tabletop versus tablet PC, affects fraction learning. Two groups, a control and experimental, were assigned. Control students have learned fraction by using tablet…

Code-Hopping Based Transmission Scheme for Wireless Physical-Layer Security

Directory of Open Access Journals (Sweden)

Liuguo Yin

2018-01-01

Full Text Available Due to the broadcast and time-varying natures of wireless channels, traditional communication systems that provide data encryption at the application layer suffer many challenges such as error diffusion. In this paper, we propose a code-hopping based secrecy transmission scheme that uses dynamic nonsystematic low-density parity-check (LDPC codes and automatic repeat-request (ARQ mechanism to jointly encode and encrypt source messages at the physical layer. In this scheme, secret keys at the transmitter and the legitimate receiver are generated dynamically upon the source messages that have been transmitted successfully. During the transmission, each source message is jointly encoded and encrypted by a parity-check matrix, which is dynamically selected from a set of LDPC matrices based on the shared dynamic secret key. As for the eavesdropper (Eve, the uncorrectable decoding errors prevent her from generating the same secret key as the legitimate parties. Thus she cannot select the correct LDPC matrix to recover the source message. We demonstrate that our scheme can be compatible with traditional cryptosystems and enhance the security without sacrificing the error-correction performance. Numerical results show that the bit error rate (BER of Eve approaches 0.5 as the number of transmitted source messages increases and the security gap of the system is small.

Switched diversity strategies for dual-hop amplify-and-forward relaying systems

KAUST Repository

Gaaloul, Fakhreddine; Radaydeh, Redha Mahmoud Mesleh; Alouini, Mohamed-Slim

2012-01-01

This study investigates different receive single-branch switch-based diversity schemes for dual-hop amplify-and-forward relaying networks. Specifically, three receive processing algorithms are adopted, in which the receive branch is selected using

Respiratory disease associated with occupational inhalation to hop (Humulus lupulus) during harvest and processing.

Science.gov (United States)

Reeb-Whitaker, Carolyn K; Bonauto, David K

2014-11-01

There is little published evidence for occupational respiratory disease caused by hop dust inhalation. In the United States, hops are commercially produced in the Pacific Northwest region. To describe occupational respiratory disease in hop workers. Washington State workers' compensation claims filed by hop workers for respiratory disease were systematically identified and reviewed. Incidence rates of respiratory disease in hop workers were compared with rates in field vegetable crop farm workers. Fifty-seven cases of respiratory disease associated with hop dust inhalation were reported from 1995 to 2011. Most cases (61%) were diagnosed by the attending health care practitioner as having work-related asthma. Seven percent of cases were diagnosed as chronic obstructive pulmonary disease, and the remaining cases were diagnosed as allergic respiratory disorders (eg, allergic rhinitis) or asthma-associated symptoms (eg, dyspnea). Cases were associated with hop harvesting, secondary hop processing, and indirect exposure. The incidence rate of respiratory disease in hop workers was 15 cases per 10,000 full-time workers, which was 30 times greater than the incidence rate for field vegetable crop workers. A strong temporal association between hop dust exposure and respiratory symptoms and a clear association between an increase in hop dust concentrations and the clinical onset of symptoms were apparent in 3 cases. Occupational exposure to hop dust is associated with respiratory disease. Respiratory disease rates were higher in hop workers than in a comparison group of agricultural workers. Additional research is needed before hop dust can be confirmed as a causative agent for occupational asthma. Copyright © 2014 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Let Me Blow Your Mind: Hip Hop Feminist Futures in Theory and Praxis

Science.gov (United States)

Lindsey, Treva B.

2015-01-01

This essay brings together key theoretical interventions in hip-hop feminism to explore the continued, but undervalued, significance of hip-hop feminism in urban education. More specifically, the essay challenges narrow conceptualizations of the "hip hop subject" as Black and male by using hip-hop feminist theory to incorporate the lived…

Hopping conductivity via deep impurity states in InP

International Nuclear Information System (INIS)

Kuznetsov, V.P.; Messerer, M.A.; Omel'yanovskij, Eh.M.

1984-01-01

Hopping (epsilon 3 ) and Mott conductivities via deep impurity compounds with localization radius below 10 A have been studied using as an example Mn in InP. It is shown, that the existing theory of hopping conductivity in low-alloyed semiconductors with Na 3 << 1 can be Used for the case of deep centres as successfully as for the case of insignificant hydrogen-like impurities. Fundamental parameters of the theory: localization radius of wave function of deep impurities, state density near the Fermi level, mean hop length, are determined

Comparison of Low-Complexity Diversity Schemes for Dual-Hop AF Relaying Systems

KAUST Repository

Gaaloul, Fakhreddine; Alouini, Mohamed-Slim; Radaydeh, Redha M.

2012-01-01

This paper investigates the performance of two low-complexity combining schemes, which are based on one- or two-phase observation, to mitigate multipath fading in dual-hop amplify-and-forward relaying systems. For the one-phase-based combining, a

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI

Directory of Open Access Journals (Sweden)

Ling-Li Zeng

2018-04-01

Full Text Available Background: A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. Methods: A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Findings: Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. Interpretation: The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the “disconnectivity” model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Keywords: Schizophrenia, Deep learning, Connectome, f

Framing Hip Hop: New Methodologies for New Times

Science.gov (United States)

Dimitriadis, Greg

2015-01-01

This article revisits the central impulse behind early advocacy for ethnographic approaches to hip hop--that critics should try as much as possible to limit their own certainties around what hip hop can and might mean. While ethnographic approaches can engender the kinds of personal dislocations that allow for this negotiation, they do not…

Hip-Hop as a Resource for Understanding the Urban Context: A Review of Christopher Edmin's--Science Education for the Hip-Hop Generation, Sense Publishers, Rotterdam, 2010

Science.gov (United States)

Brown, Bryan

2010-01-01

This review explores Edmin's "Science education for the hip-hop generation" by documenting how he frames hip-hop as a means to access urban student culture. He argues that hip-hop is more than a mere music genre, but rather a culture that provides young people with ways of connecting to the world. Two primary ideas emerged as central to…

Multi-agent system for Knowledge-based recommendation of Learning Objects

Directory of Open Access Journals (Sweden)

Paula Andrea RODRÍGUEZ MARÍN

2015-12-01

Full Text Available Learning Object (LO is a content unit being used within virtual learning environments, which -once found and retrieved- may assist students in the teaching - learning process. Such LO search and retrieval are recently supported and enhanced by data mining techniques. In this sense, clustering can be used to find groups holding similar LOs so that from obtained groups, knowledge-based recommender systems (KRS can recommend more adapted and relevant LOs. In particular, prior knowledge come from LOs previously selected, liked and ranked by the student to whom the recommendation will be performed. In this paper, we present a KRS for LOs, which uses a conventional clustering technique, namely K-means, aimed at finding similar LOs and delivering resources adapted to a specific student. Obtained promising results show that proposed KRS is able to both retrieve relevant LO and improve the recommendation precision.Learning Object (LO is a content unit being used within virtual learning environments, which -once found and retrieved- may assist students in the teaching - learning process. Such LO search and retrieval are recently supported and enhanced by data mining techniques. In this sense, clustering can be used to find groups holding similar LOs so that from obtained groups, knowledge-based recommender systems (KRS can recommend more adapted and relevant LOs. In particular, prior knowledge come from LOs previously selected, liked and ranked by the student to whom the recommendation will be performed. In this paper, we present a KRS for LOs, which uses a conventional clustering technique, namely K-means, aimed at finding similar LOs and delivering resources adapted to a specific student. Obtained promising results show that proposed KRS is able to both retrieve relevant LO and improve the recommendation precision.

Multi-Label Learning via Random Label Selection for Protein Subcellular Multi-Locations Prediction.

Science.gov (United States)

Wang, Xiao; Li, Guo-Zheng

2013-03-12

Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multi-location proteins to multiple proteins with single location, which doesn't take correlations among different subcellular locations into account. In this paper, a novel method named RALS (multi-label learning via RAndom Label Selection), is proposed to learn from multi-location proteins in an effective and efficient way. Through five-fold cross validation test on a benchmark dataset, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark datasets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multi-locations of proteins. The prediction web server is available at http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage.

A two-hop based adaptive routing protocol for real-time wireless sensor networks.

Science.gov (United States)

Rachamalla, Sandhya; Kancherla, Anitha Sheela

2016-01-01

One of the most important and challenging issues in wireless sensor networks (WSNs) is to optimally manage the limited energy of nodes without degrading the routing efficiency. In this paper, we propose an energy-efficient adaptive routing mechanism for WSNs, which saves energy of nodes by removing the much delayed packets without degrading the real-time performance of the used routing protocol. It uses the adaptive transmission power algorithm which is based on the attenuation of the wireless link to improve the energy efficiency. The proposed routing mechanism can be associated with any geographic routing protocol and its performance is evaluated by integrating with the well known two-hop based real-time routing protocol, PATH and the resulting protocol is energy-efficient adaptive routing protocol (EE-ARP). The EE-ARP performs well in terms of energy consumption, deadline miss ratio, packet drop and end-to-end delay.

Human fatigue expression recognition through image-based dynamic multi-information and bimodal deep learning

Science.gov (United States)

Zhao, Lei; Wang, Zengcai; Wang, Xiaojin; Qi, Yazhou; Liu, Qing; Zhang, Guoxin

2016-09-01

Human fatigue is an important cause of traffic accidents. To improve the safety of transportation, we propose, in this paper, a framework for fatigue expression recognition using image-based facial dynamic multi-information and a bimodal deep neural network. First, the landmark of face region and the texture of eye region, which complement each other in fatigue expression recognition, are extracted from facial image sequences captured by a single camera. Then, two stacked autoencoder neural networks are trained for landmark and texture, respectively. Finally, the two trained neural networks are combined by learning a joint layer on top of them to construct a bimodal deep neural network. The model can be used to extract a unified representation that fuses landmark and texture modalities together and classify fatigue expressions accurately. The proposed system is tested on a human fatigue dataset obtained from an actual driving environment. The experimental results demonstrate that the proposed method performs stably and robustly, and that the average accuracy achieves 96.2%.

Computational micromechanics analysis of electron hopping and interfacial damage induced piezoresistive response in carbon nanotube-polymer nanocomposites

International Nuclear Information System (INIS)

Chaurasia, A K; Seidel, G D; Ren, X

2014-01-01

Carbon nanotube (CNT)-polymer nanocomposites have been observed to exhibit an effective macroscale piezoresistive response, i.e., change in macroscale resistivity when subjected to applied deformation. The macroscale piezoresistive response of CNT-polymer nanocomposites leads to deformation/strain sensing capabilities. It is believed that the nanoscale phenomenon of electron hopping is the major driving force behind the observed macroscale piezoresistivity of such nanocomposites. Additionally, CNT-polymer nanocomposites provide damage sensing capabilities because of local changes in electron hopping pathways at the nanoscale because of initiation/evolution of damage. The primary focus of the current work is to explore the effect of interfacial separation and damage at the nanoscale CNT-polymer interface on the effective macroscale piezoresistive response. Interfacial separation and damage are allowed to evolve at the CNT-polymer interface through coupled electromechanical cohesive zones, within a finite element based computational micromechanics framework, resulting in electron hopping based current density across the separated CNT-polymer interface. The macroscale effective material properties and gauge factors are evaluated using micromechanics techniques based on electrostatic energy equivalence. The impact of the electron hopping mechanism, nanoscale interface separation and damage evolution on the effective nanocomposite electrostatic and piezoresistive response is studied in comparison with the perfectly bonded interface. The effective electrostatic/piezoresistive response for the perfectly bonded interface is obtained based on a computational micromechanics model developed in the authors’ earlier work. It is observed that the macroscale effective gauge factors are highly sensitive to strain induced formation/disruption of electron hopping pathways, interface separation and the initiation/evolution of interfacial damage. (paper)

Perceptions of the motivational climate, need satisfaction, and indices of well- and ill-being among hip hop dancers.

Science.gov (United States)

Quested, Eleanor; Duda, Joan L

2009-01-01

Grounded in the self-determination theoretical framework (SDT) formulated by Deci and Ryan, and specifically the basic needs mini-theory (BNT), this study examined the relationship between perceptions of the motivational climate manifested in hip hop environments, satisfaction of the three basic needs, and indicators of well- and ill-being among hip hop dancers. Fifty-nine hip hop dancers (mean age: 20.29 years) completed a questionnaire assessing the variables of interest in the study. Perceptions of a task-involving climate were positively associated with satisfaction of the needs for autonomy, competence, and relatedness. Perceptions of an ego-involving climate negatively predicted relatedness. Satisfaction of the need for competence was positively associated with positive affect, and negatively linked to negative affect. Competence need satisfaction significantly mediated the relationship between a perceived task-involving climate and positive and negative affective states. In sum, the findings provided partial support for the facets of SDT and BNT. The results also indicated that promoting the task-involving features of dance learning environments may be beneficial to dancers' well-being.

Electrolytic conductivity-the hopping mechanism of the proton and beyond

International Nuclear Information System (INIS)

Gileadi, E.; Kirowa-Eisner, E.

2006-01-01

The hopping mechanism of electrolytic conductivity is analyzed, employing mixtures of two solvents: one that sustains the hopping mechanism and the other that does not inhibit it directly, but interferes with it by diluting the solvent that sustains hopping. Measurement of the equivalent conductivity shows that the excess proton conductivities of H 3 O + and OH - increases with increasing temperature, although the number of hydrogen bonds is known to decrease. In mixtures of acetonitrile with water, proton hopping does not start until a threshold concentration of about 20 vol.% water has been reached, while no such threshold concentration is observed upon addition of methanol to acetonitrile. It is concluded that in the former the proton is transferred to a cluster of water molecules, which can be formed only if there is enough water in the solvent mixture. This observation leads to the concept of mono-water, which is the state of water molecules when they constitute a small minority in the solvent mixtures, as opposed to bulk water, which consists of clusters of variable sizes. Systems in which a hopping mechanism of heavy ions has been observed include Br - /Br 2 and I - /I 2 . In these cases the triple ions Br 3 - and I 3 - , respectively are formed, and serve as the mediators for the transfer of the simple halogen ion. A very large increase of conductivity was observed upon solidification of the Br - /Br 3 - system, probably caused by favorable linear alignment of ions in the solid. The conductivity of acidified methanol decreases upon addition of water, because the affinity of the proton to water is higher than to methanol, thus water can act as a scavenger for protons. This behavior exemplifies a general observation, namely that conductivity by hopping can only occur when the Gibbs energy of the system does not change significantly following ion transfer; otherwise the ions would be trapped in the more stable state, hindering further propagation by hopping

Multi-modal Social Networks: A MRF Learning Approach

Science.gov (United States)

2016-06-20

Network forensics: random infection vs spreading epidemic , Proceedings of ACM Sigmetrics. 11-JUN-12, London, UK. : , TOTAL: 4 06/09/2016 Received Paper...Multi-modal Social Networks A MRF Learning Approach The work primarily focused on two lines of research. 1. We propose new greedy algorithms...Box 12211 Research Triangle Park, NC 27709-2211 social networks , learning and inference REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT

Electron hopping through proteins

Czech Academy of Sciences Publication Activity Database

Warren, J. J.; Ener, M. E.; Vlček, Antonín; Winkler, J. R.; Gray, H. B.

2012-01-01

Roč. 256, 21-22 (2012), s. 2478-2487 ISSN 0010-8545 R&D Projects: GA MŠk(CZ) ME10124 Institutional support: RVO:61388955 Keywords : electron transfer * multistep tunneling * hopping maps Subject RIV: CG - Electrochemistry Impact factor: 11.016, year: 2012

Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

Science.gov (United States)

Dickes, Amanda Catherine; Sengupta, Pratim

2013-01-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these…

Gene ontology based transfer learning for protein subcellular localization

Directory of Open Access Journals (Sweden)

Zhou Shuigeng

2011-02-01

Full Text Available Abstract Background Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as GO, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the GO terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology. Results In this paper, we propose a Gene Ontology Based Transfer Learning Model (GO-TLM for large-scale protein subcellular localization. The model transfers the signature-based homologous GO terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false GO terms that are resulted from evolutionary divergence. We derive three GO kernels from the three aspects of gene ontology to measure the GO similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

Science.gov (United States)

Zeng, Ling-Li; Wang, Huaning; Hu, Panpan; Yang, Bo; Pu, Weidan; Shen, Hui; Chen, Xingui; Liu, Zhening; Yin, Hong; Tan, Qingrong; Wang, Kai; Hu, Dewen

2018-04-01

A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources) was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the "disconnectivity" model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Copyright © 2018 German Center for Neurodegenerative Diseases (DZNE). Published by Elsevier B.V. All rights reserved.

Educative Processes in the Hip Hop: the celebration of the values of the community

Directory of Open Access Journals (Sweden)

Cristiano Tierno Siqueira

2010-05-01

Full Text Available The objective of this inquiry was to understand and systemize the Educative Processes that characterize Practical the Social one of the Hip Hop of the city of São Carlos, interior of São Paulo; as these young ones if educate and as they educate other people of its communities, longing for to contribute for the valuation of the Movements of Youth and for the elaboration of politics that consider them. For in such a way, we follow some of its activities, as periodic weekly meetings, artistic events, educative activities and parties. The analysis of the data disclosed to some values gifts in the life of these people, as the love for what it becomes, the not arrogant, the necessity of the collective work, the responsibility and the belonging to a community. The men and the women of the Hip Hop invite-in opening the doors of the Schools and University, so that in we let us exempt them of the preconceptions that we construct every day, so that we learn with young of the Hip Hop, as well as with other people who fight for worthy conditions of life. We believe that this inquiry brings contributions to think the education that characterize Practical Social in not-pertaining to school spaces, as well as to rethink the education in the pertaining to school spaces.

Population dynamics and integrated control of the damson-hop aphid Phorodon humuli (Schrank on hops in Spain

Directory of Open Access Journals (Sweden)

A. Lorenzana

2013-04-01

Full Text Available The hop aphid Phorodon humuli (Schrank (Hemiptera: Aphididae is a serious pest in most areas where hops are grown. A field trial was performed on a hop yard throughout 2002, 2003 and 2004 in León (Spain in order to analyse the population development of Phorodon humuli and its natural enemies, as well as to determine the most effective integrated program of insecticide treatments. The basic population development pattern of P. humuli was similar in the three years: the population peaked between mid to late June, and then decreased in late June/early July, rising again and reaching another peak in mid-July, after which it began to decline, rising once more in late August; this last rise is characteristic of Spain and has not been recorded in the rest of Europe. The hop aphid’s main natural enemy found on the leaves was Coccinella septempunctata (Coleoptera: Coccinellidae. The multiple regression analysis showed that aphids are positively related with the presence of beetle eggs and mean daily temperatures and negatively related with maximum daily temperature integral above 27ºC in plots without insecticide treatment. The most effective program of insecticide (imidacloprid treatments consisted of an initial treatment in June and a second treatment in the second half of July or at the beginning of August. However, a single treatment in June would be sufficient when in this last period the maximum daily temperatures were higher than 27ºC for at least 15 days, avoiding in this way the harmful effects of imidacloprid on predators.

Hop/STI1 modulates retinal proliferation and cell death independent of PrPC

International Nuclear Information System (INIS)

Arruda-Carvalho, Maithe; Njaine, Brian; Silveira, Mariana S.; Linden, Rafael; Chiarini, Luciana B.

2007-01-01

Hop/STI1 is a co-chaperone adaptor protein for Hsp70/Hsp90 complexes. Hop/STI1 is found extracellularly and modulates cell death and differentiation through interaction with the prion protein (PrP C ). Here, we investigated the expression of hop/STI1 and its role upon cell proliferation and cell death in the developing retina. Hop/STI1 is more expressed in developing rat retina than in the mature tissue. Hop/STI1 blocks retinal cell death in the neuroblastic layer (NBL) in a PrP C dependent manner, but failed to protect ganglion cells against axotomy-induced cell death. An antibody raised against hop/STI1 (α-STI1) blocked both ganglion cell and NBL cell death independent of PrP C . cAMP/PKA, ERK, PI3K and PKC signaling pathways were not involved in these effects. Hop/STI1 treatment reduced proliferation, while α-STI1 increased proliferation in the developing retina, both independent of PrP C . We conclude that hop/STI1 can modulate both proliferation and cell death in the developing retina independent of PrP C

Hopping models and ac universality

DEFF Research Database (Denmark)

Dyre, Jeppe; Schrøder, Thomas

2002-01-01

Some general relations for hopping models are established. We proceed to discuss the universality of the ac conductivity which arises in the extreme disorder limit of the random barrier model. It is shown that the relevant dimension entering into the diffusion cluster approximation (DCA) is the h......Some general relations for hopping models are established. We proceed to discuss the universality of the ac conductivity which arises in the extreme disorder limit of the random barrier model. It is shown that the relevant dimension entering into the diffusion cluster approximation (DCA......) is the harmonic (fracton) dimension of the diffusion cluster. The temperature scaling of the dimensionless frequency entering into the DCA is discussed. Finally, some open problems regarding ac universality are listed....

Understanding Mott's law from scaling of variable-range-hopping currents and intrinsic current fluctuations

NARCIS (Netherlands)

Pasveer, W.F.; Michels, M.A.J.

2006-01-01

We have used the master equation to simulate variable-range hopping (VRH) of charges in a strongly disordered d-dimensional energy landscape (d=1,2,3). The current distribution over hopping distances and hopping energies gives a clear insight into the difference between hops that occur most

Climate, weather, and hops

Science.gov (United States)

As climate and weather become more variable, hop growers face increased uncertainty in making decisions about their crop. Given the unprecedented nature of these changes, growers may no longer have enough information and intuitive understanding to adequately assess the situation and evaluate their m...

Learning preferences and attitudes by multi-criteria overlap dominance and relevance functions

DEFF Research Database (Denmark)

Franco de los Ríos, Camilo; Hougaard, Jens Leth; Nielsen, Kurt

2018-01-01

This paper proposes an interval-valued multi-criteria method for learning preferences and attitudes, identifying priorities with maximal robustness for decision support. The method is based on the notion of weighted overlap dominance, formalized by means of aggregation operators and interval......-valued fuzzy sets. The procedure handles uncertainty by estimating the likelihood of dominance among pairs of alternatives, inducing an attitude-based system of dominance and indifference relations. This system allows conflicting situations of indifference/dependency to arise, which need to be resolved...... for properly identifying preferences under any attitude. In order to do so, relevance functions are examined over the whole system of relations, obtaining a weak preference order together with its associated attitude and robustness index. As a result, the proposed method allows learning preferences...

High Order Differential Frequency Hopping: Design and Analysis

Directory of Open Access Journals (Sweden)

Yong Li

2015-01-01

Full Text Available This paper considers spectrally efficient differential frequency hopping (DFH system design. Relying on time-frequency diversity over large spectrum and high speed frequency hopping, DFH systems are robust against hostile jamming interference. However, the spectral efficiency of conventional DFH systems is very low due to only using the frequency of each channel. To improve the system capacity, in this paper, we propose an innovative high order differential frequency hopping (HODFH scheme. Unlike in traditional DFH where the message is carried by the frequency relationship between the adjacent hops using one order differential coding, in HODFH, the message is carried by the frequency and phase relationship using two-order or higher order differential coding. As a result, system efficiency is increased significantly since the additional information transmission is achieved by the higher order differential coding at no extra cost on either bandwidth or power. Quantitative performance analysis on the proposed scheme demonstrates that transmission through the frequency and phase relationship using two-order or higher order differential coding essentially introduces another dimension to the signal space, and the corresponding coding gain can increase the system efficiency.

The significance of the grasshopper effect on the atmospheric distribution of persistent organic substances

Science.gov (United States)

Semeena, V. S.; Lammel, Gerhard

2005-04-01

Slowly degradable, semivolatile organic compounds (SOCs) may undergo more than one volatilization-transport-deposition cycle through the atmosphere (multi-hopping). The significance of this process for the potential for long-range transport (LRT) is addressed for the first time. We use a multicompartment model which in turn is based on a general circulation model. The results suggest that both transport by single-hopping and multi-hopping contribute significantly to LRT of DDT and γ-HCH (lindane) and to accumulation in high latitudes. A larger fraction of the molecules transported by multi-hopping than of the molecules transported by single-hopping is deposited to the world's oceans. Multi-hopping prevails in the boundary layer far from the source regions. However, single-hopping contributes an almost equal amount to the deposition of DDT and γ-HCH in the Arctic.

Hopping system control with an approximated dynamics model and upper-body motion

Energy Technology Data Exchange (ETDEWEB)

Lee, Hyang Jun; Oh, Jun Ho [KAIST, Daejeon (Korea, Republic of)

2015-11-15

A hopping system is highly non-linear due to the nature of its dynamics, which has alternating phases in a cycle, flight and stance phases and related transitions. Every control method that stabilizes the hopping system satisfies the Poincaré stability condition. At the Poincaré section, a hopping system cycle is considered as discrete sectional data set. By controlling the sectional data in a discrete control form, we can generate a stable hopping cycle. We utilize phase-mapping matrices to build a Poincaré return map by approximating the dynamics of the hopping system with SLIP model. We can generate various Poincaré stable gait patterns with the approximated discrete control form which uses upper-body motions as inputs.

Investigating Cultural Collision: Educators' Perceptions of Hip-Hop Culture

Science.gov (United States)

Beachum, Floyd D.

2013-01-01

Hip-hop music has been embraced worldwide by youth, pummeled in the media for supposedly increasing social misery and hailed as a significant musical breakthrough. Hip-hop culture has transcended musical boundaries and now impacts speech, clothing, mannerisms, movies, websites, television programming, magazines, and energy drinks (Dyson, 2007;…

Degradation of hop bitter acids by fungi

International Nuclear Information System (INIS)

Huszcza, Ewa; Bartmanska, Agnieszka; Aniol, Miroslaw; Maczka, Wanda; Zolnierczyk, Anna; Wawrzenczyk, Czeslaw

2008-01-01

Nine fungal strains related to: Trametes versicolor, Nigrospora oryzae, Inonotus radiatus, Crumenulopsis sororia, Coryneum betulinum, Cryptosporiopsis radicicola, Fusarium equiseti, Rhodotorula glutinis and Candida parapsilosis were tested for their ability to degrade humulones and lupulones. The best results were obtained for T. versicolor culture, in which humulones and lupulones were fully degraded after 4 days of incubation in the dark or after 36 h in the light. The experiments were performed on a commercial hop extract and on sterilized spent hops

A new method of hybrid frequency hopping signals selection and blind parameter estimation

Science.gov (United States)

Zeng, Xiaoyu; Jiao, Wencheng; Sun, Huixian

2018-04-01

Frequency hopping communication is widely used in military communications at home and abroad. In the case of single-channel reception, it is scarce to process multiple frequency hopping signals both effectively and simultaneously. A method of hybrid FH signals selection and blind parameter estimation is proposed. The method makes use of spectral transformation, spectral entropy calculation and PRI transformation basic theory to realize the sorting and parameter estimation of the components in the hybrid frequency hopping signal. The simulation results show that this method can correctly classify the frequency hopping component signal, and the estimated error of the frequency hopping period is about 5% and the estimated error of the frequency hopping frequency is less than 1% when the SNR is 10dB. However, the performance of this method deteriorates seriously at low SNR.

From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification

Science.gov (United States)

2010-01-01

Background Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification. Results In view of learning in a taxonomic framework, we consider two types of trees. First, a FAME tree is constructed with a supervised divisive clustering algorithm. Subsequently, based on 16S rRNA gene sequence analysis, phylogenetic trees are inferred by the NJ and UPGMA methods. In this second approach, the species classification problem is based on the combination of two different types of data. Herein, 16S rRNA gene sequence data is used for phylogenetic tree inference and the corresponding binary tree splits are learned based on FAME data. We call this learning approach 'phylogenetic learning'. Supervised Random Forest models are developed to train the classification tasks in a stratified cross-validation setting. In this way, better classification results are obtained for species that are typically hard to distinguish by a single or flat multi-class classification model. Conclusions FAME-based bacterial species classification is successfully evaluated in a taxonomic framework. Although the proposed approach does not improve the overall accuracy compared to flat multi-class classification, it has some distinct advantages. First, it has better capabilities for distinguishing species on which flat multi-class classification fails. Secondly, the hierarchical classification structure allows to easily evaluate and visualize the resolution of FAME data for

From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification

Directory of Open Access Journals (Sweden)

Dawyndt Peter

2010-01-01

Full Text Available Abstract Background Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification. Results In view of learning in a taxonomic framework, we consider two types of trees. First, a FAME tree is constructed with a supervised divisive clustering algorithm. Subsequently, based on 16S rRNA gene sequence analysis, phylogenetic trees are inferred by the NJ and UPGMA methods. In this second approach, the species classification problem is based on the combination of two different types of data. Herein, 16S rRNA gene sequence data is used for phylogenetic tree inference and the corresponding binary tree splits are learned based on FAME data. We call this learning approach 'phylogenetic learning'. Supervised Random Forest models are developed to train the classification tasks in a stratified cross-validation setting. In this way, better classification results are obtained for species that are typically hard to distinguish by a single or flat multi-class classification model. Conclusions FAME-based bacterial species classification is successfully evaluated in a taxonomic framework. Although the proposed approach does not improve the overall accuracy compared to flat multi-class classification, it has some distinct advantages. First, it has better capabilities for distinguishing species on which flat multi-class classification fails. Secondly, the hierarchical classification structure allows to easily evaluate and visualize the

From learning taxonomies to phylogenetic learning: integration of 16S rRNA gene data into FAME-based bacterial classification.

Science.gov (United States)

Slabbinck, Bram; Waegeman, Willem; Dawyndt, Peter; De Vos, Paul; De Baets, Bernard

2010-01-30

Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification. In view of learning in a taxonomic framework, we consider two types of trees. First, a FAME tree is constructed with a supervised divisive clustering algorithm. Subsequently, based on 16S rRNA gene sequence analysis, phylogenetic trees are inferred by the NJ and UPGMA methods. In this second approach, the species classification problem is based on the combination of two different types of data. Herein, 16S rRNA gene sequence data is used for phylogenetic tree inference and the corresponding binary tree splits are learned based on FAME data. We call this learning approach 'phylogenetic learning'. Supervised Random Forest models are developed to train the classification tasks in a stratified cross-validation setting. In this way, better classification results are obtained for species that are typically hard to distinguish by a single or flat multi-class classification model. FAME-based bacterial species classification is successfully evaluated in a taxonomic framework. Although the proposed approach does not improve the overall accuracy compared to flat multi-class classification, it has some distinct advantages. First, it has better capabilities for distinguishing species on which flat multi-class classification fails. Secondly, the hierarchical classification structure allows to easily evaluate and visualize the resolution of FAME data for the discrimination of bacterial

The effect of correlations on the non-ohmic behavior of the small-polaron hopping conductivity in 1D and 3D disordered systems

International Nuclear Information System (INIS)

Dimakogianni, M; Triberis, G P

2010-01-01

According to percolation theory the investigation of charge transport in disordered systems is equivalent to the study of the possibility of the passage of the carriers through a random network of impedances which interconnect the different lattice sites. When the site energies are not the same, the energy of a site affects the incoming as well as the outgoing impedances connected to the given site and this gives rise to correlations between neighboring impedances. This new condition characterizes the transport process and imposes the evaluation of the average number of sites accessible by a bond from a given site for all possible configurations of sites that satisfy the percolation condition. The generalized molecular crystal model, appropriate for the study of small-polaron hopping transport in disordered systems, and the Kubo formula permit the evaluation of these impedances. Taking correlations into account, theoretical percolation considerations applicable to one-dimensional and three-dimensional disordered systems, lead to analytical expressions for the temperature and electric field dependence of the DC conductivity at high (multi-phonon-assisted hopping) and low (few-phonon-assisted hopping) temperatures. The theoretical analysis reveals the effect of correlations on the non-ohmic behavior of the small-polaron hopping conductivity and permits the evaluation of the maximum hopping distance. Quantitative estimates of this effect are presented comparing the theoretical results, including correlations with those ignoring them, previously reported, applying them to recent experimental data for a wide temperature range and from low up to moderate electric fields.

Crossover in tunneling hops in systems of strongly localized electrons

International Nuclear Information System (INIS)

Lien Nguyen, V.; Gamietea, A.D.

1995-11-01

Accurate Monte-Carlo simulation data show a consistent crossover in different characters of tunneling hops in two-dimensional systems of strongly localized electrons in the presence of scattering and quantum interference of hopping paths. The results also suggest a negative answer to the question whether there is a two-dimensional sign phase transition. The fractal behaviour observed in the direction perpendicular to the hopping direction is found to be similar to that for eigenstates in one-dimensional localized systems. (author). 16 refs, 6 figs

Hsp70/Hsp90 organising protein (hop): beyond interactions with chaperones and prion proteins.

Science.gov (United States)

Baindur-Hudson, Swati; Edkins, Adrienne L; Blatch, Gregory L

2015-01-01

The Hsp70/Hsp90 organising protein (Hop), also known as stress-inducible protein 1 (STI1), has received considerable attention for diverse cellular functions in both healthy and diseased states. There is extensive evidence that intracellular Hop is a co-chaperone of the major chaperones Hsp70 and Hsp90, playing an important role in the productive folding of Hsp90 client proteins. Consequently, Hop is implicated in a number of key signalling pathways, including aberrant pathways leading to cancer. However, Hop is also secreted and it is now well established that Hop also serves as a receptor for the prion protein, PrP(C). The intracellular and extracellular forms of Hop most likely represent two different isoforms, although the molecular determinants of these divergent functions are yet to be identified. There is also a growing body of research that reports the involvement of Hop in cellular activities that appear independent of either chaperones or PrP(C). While Hop has been shown to have various cellular functions, its biological function remains elusive. However, recent knockout studies in mammals suggest that Hop has an important role in embryonic development. This review provides a critical overview of the latest molecular, cellular and biological research on Hop, critically evaluating its function in healthy systems and how this function is adapted in diseases states.

The Influence of Ecological and Conventional Plant Production Systems on Soil Microbial Quality under Hops (Humulus lupulus)

Science.gov (United States)

Oszust, Karolina; Frąc, Magdalena; Gryta, Agata; Bilińska, Nina

2014-01-01

The knowledge about microorganisms—activity and diversity under hop production is still limited. We assumed that, different systems of hop production (within the same soil and climatic conditions) significantly influence on the composition of soil microbial populations and its functional activity (metabolic potential). Therefore, we compared a set of soil microbial properties in the field experiment of two hop production systems (a) ecological based on the use of probiotic preparations and organic fertilization (b) conventional—with the use of chemical pesticides and mineral fertilizers. Soil analyses included following microbial properties: The total number microorganisms, a bunch of soil enzyme activities, the catabolic potential was also assessed following Biolog EcoPlates®. Moreover, the abundance of ammonia-oxidizing archaea (AOA) was characterized by terminal restriction fragment length polymorphism analysis (T-RFLP) of PCR ammonia monooxygenase α-subunit (amoA) gene products. Conventional and ecological systems of hop production were able to affect soil microbial state in different seasonal manner. Favorable effect on soil microbial activity met under ecological, was more probably due to livestock-based manure and fermented plant extracts application. No negative influence on conventional hopyard soil was revealed. Both type of production fulfilled fertilizing demands. Under ecological production it was due to livestock-based manure fertilizers and fermented plant extracts application. PMID:24897025

The Influence of Ecological and Conventional Plant Production Systems on Soil Microbial Quality under Hops (Humulus lupulus

Directory of Open Access Journals (Sweden)

Karolina Oszust

2014-06-01

Full Text Available The knowledge about microorganisms—activity and diversity under hop production is still limited. We assumed that, different systems of hop production (within the same soil and climatic conditions significantly influence on the composition of soil microbial populations and its functional activity (metabolic potential. Therefore, we compared a set of soil microbial properties in the field experiment of two hop production systems (a ecological based on the use of probiotic preparations and organic fertilization (b conventional—with the use of chemical pesticides and mineral fertilizers. Soil analyses included following microbial properties: The total number microorganisms, a bunch of soil enzyme activities, the catabolic potential was also assessed following Biolog EcoPlates®. Moreover, the abundance of ammonia-oxidizing archaea (AOA was characterized by terminal restriction fragment length polymorphism analysis (T-RFLP of PCR ammonia monooxygenase α-subunit (amoA gene products. Conventional and ecological systems of hop production were able to affect soil microbial state in different seasonal manner. Favorable effect on soil microbial activity met under ecological, was more probably due to livestock-based manure and fermented plant extracts application. No negative influence on conventional hopyard soil was revealed. Both type of production fulfilled fertilizing demands. Under ecological production it was due to livestock-based manure fertilizers and fermented plant extracts application.

Surface hopping simulation of vibrational predissociation of methanol dimer

Science.gov (United States)

Jiang, Ruomu; Sibert, Edwin L.

2012-06-01

The mixed quantum-classical surface hopping method is applied to the vibrational predissociation of methanol dimer, and the results are compared to more exact quantum calculations. Utilizing the vibrational SCF basis, the predissociation problem is cast into a curve crossing problem between dissociative and quasibound surfaces with different vibrational character. The varied features of the dissociative surfaces, arising from the large amplitude OH torsion, generate rich predissociation dynamics. The fewest switches surface hopping algorithm of Tully [J. Chem. Phys. 93, 1061 (1990), 10.1063/1.459170] is applied to both diabatic and adiabatic representations. The comparison affords new insight into the criterion for selecting the suitable representation. The adiabatic method's difficulty with low energy trajectories is highlighted. In the normal crossing case, the diabatic calculations yield good results, albeit showing its limitation in situations where tunneling is important. The quadratic scaling of the rates on coupling strength is confirmed. An interesting resonance behavior is identified and is dealt with using a simple decoherence scheme. For low lying dissociative surfaces that do not cross the quasibound surface, the diabatic method tends to overestimate the predissociation rate whereas the adiabatic method is qualitatively correct. Analysis reveals the major culprits involve Rabi-like oscillation, treatment of classically forbidden hops, and overcoherence. Improvements of the surface hopping results are achieved by adopting a few changes to the original surface hopping algorithms.

An auxiliary graph based dynamic traffic grooming algorithm in spatial division multiplexing enabled elastic optical networks with multi-core fibers

Science.gov (United States)

Zhao, Yongli; Tian, Rui; Yu, Xiaosong; Zhang, Jiawei; Zhang, Jie

2017-03-01

A proper traffic grooming strategy in dynamic optical networks can improve the utilization of bandwidth resources. An auxiliary graph (AG) is designed to solve the traffic grooming problem under a dynamic traffic scenario in spatial division multiplexing enabled elastic optical networks (SDM-EON) with multi-core fibers. Five traffic grooming policies achieved by adjusting the edge weights of an AG are proposed and evaluated through simulation: maximal electrical grooming (MEG), maximal optical grooming (MOG), maximal SDM grooming (MSG), minimize virtual hops (MVH), and minimize physical hops (MPH). Numeric results show that each traffic grooming policy has its own features. Among different traffic grooming policies, an MPH policy can achieve the lowest bandwidth blocking ratio, MEG can save the most transponders, and MSG can obtain the fewest cores for each request.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Science.gov (United States)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Directory of Open Access Journals (Sweden)

Aichun Zhu

2018-03-01

Full Text Available This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN. Firstly, a Relative Mixture Deformable Model (RMDM is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Fast frequency hopping codes applied to SAC optical CDMA network

Science.gov (United States)

Tseng, Shin-Pin

2015-06-01

This study designed a fast frequency hopping (FFH) code family suitable for application in spectral-amplitude-coding (SAC) optical code-division multiple-access (CDMA) networks. The FFH code family can effectively suppress the effects of multiuser interference and had its origin in the frequency hopping code family. Additional codes were developed as secure codewords for enhancing the security of the network. In considering the system cost and flexibility, simple optical encoders/decoders using fiber Bragg gratings (FBGs) and a set of optical securers using two arrayed-waveguide grating (AWG) demultiplexers (DeMUXs) were also constructed. Based on a Gaussian approximation, expressions for evaluating the bit error rate (BER) and spectral efficiency (SE) of SAC optical CDMA networks are presented. The results indicated that the proposed SAC optical CDMA network exhibited favorable performance.

Frequency hopping due to acousto-electric interaction in ZnO based surface acoustic wave oscillator

Science.gov (United States)

Dasgupta, Daipayan; Sreenivas, K.

2011-08-01

A 36 MHz surface acoustic wave delay line based oscillator has been used to study the effect of acousto-electric interaction due to photo generated charge carriers in rf sputtered ZnO film under UV illumination (λ = 365 nm, 20-100 μW/cm2). Design aspects for developing a delay line based SAW oscillator are specified. The observed linear downshift in frequency (2.2 to 19.0 kHz) with varying UV intensity (20-100 μW/cm2) is related to the fractional velocity change due to acousto-electric interaction. UV illumination level of 100 μW/cm2 leads to a characteristic frequency hopping behavior arising due to a change in the oscillation criteria, and is attributed to the complex interplay between the increased attenuation and velocity shift.

A Multi-Hop Advertising Discovery and Delivering Protocol for Multi Administrative Domain MANET

Directory of Open Access Journals (Sweden)

Federico Mari

2013-01-01

Full Text Available A Mobile Ad-hoc NETwork (MANET is Multi Administrative Domain (MAD if each network node belongs to an independent authority, that is each node owns its resources and there is no central authority owning all network nodes. One of the main obstructions in designing Service Advertising, Discovery and Delivery (SADD protocol for MAD MANETs is the fact that, in an attempt to increase their own visibility, network nodes tend to flood the network with their advertisements. In this paper, we present a SADD protocol for MAD MANET, based on Bloom filters, that effectively prevents advertising floods due to such misbehaving nodes. Our results with the ns-2 simulator show that our SADD protocol is effective in counteracting advertising floods, it keeps low the collision rate as well as the energy consumption while ensuring that each peer receives all messages broadcasted by other peers.

WSN ene rgy balance multi-hop lc ustering routing algorithm%能量均衡多跳分簇路由算法

Institute of Scientific and Technical Information of China (English)

叶润; 王缓缓

2014-01-01

The lifetime of ZigBee wireless sensor network is directly related to energy consumption of nodes .In order to extend the life of the network, the clustering routing methods are used.The improved clustering routing algo-rithm-EBMHC ( energy balance multi-hop clustering routing algorithm) , which adopts centralized rotation-cluste-ring method and distributed competition method of cluster head.This makes the network’ s idle nodes sleep and cluster head node work acting as multiple transmission.It also has data fusion and routing maintenance in a single cycle, so as to make full and effective use of network energy.Hierarchical management can solve imbalance of net-work node energy consumption.The simulation shows that EBMHC algorithm outperforms LEACH and SEP, making the network energy consumption more balanced and prolonging the network lifetime.%ZigBee无线传感器网络的生存寿命与节点的能耗直接相关。为了延长网络的寿命，通常采用分簇路由方法。通过集中成簇管理以及分布簇头竞争的能量均衡多跳分簇路由算法EBMHC（ energy balance multi－hop clustering rou-ting algorithm），在一个周期内，使得网络空闲节点休眠，簇头节点担任多条传输、数据融合以及路由维护的功能，以充分有效利用网络能量。分层管理方式可以缓解网络节点能耗不均衡问题。通过仿真表明， EBMHC算法优于LEACH和SEP算法，使网络能耗更均衡，延长了网络生存周期。

Multi-modal Virtual Scenario Enhances Neurofeedback Learning

Directory of Open Access Journals (Sweden)

Avihay Cohen

2016-08-01

Full Text Available In the past decade neurofeedback has become the focus of a growing body of research. With real-time fMRI enabling on-line monitoring of emotion related areas such as the amygdala, many have begun testing its therapeutic benefits. However most existing neurofeedback procedures still use monotonic uni-modal interfaces, thus possibly limiting user engagement and weakening learning efficiency. The current study tested a novel multi-sensory neurofeedback animated scenario aimed at enhancing user experience and improving learning. We examined whether relative to a simple uni-modal 2D interface, learning via an interface of complex multi-modal 3D scenario will result in improved neurofeedback learning. As a neural-probe, we used the recently developed fMRI-inspired EEG model of amygdala activity (amygdala-EEG finger print; amygdala-EFP, enabling low-cost and mobile limbic neurofeedback training. Amygdala-EFP was reflected in the animated scenario by the unrest level of a hospital waiting-room in which virtual characters become impatient, approach the admission-desk and complain loudly. Successful down-regulation was reflected as an ease in the room unrest-level. We tested whether relative to a standard uni-modal 2D graphic thermometer interface, this animated scenario could facilitate more effective learning and improve the training experience. Thirty participants underwent two separated neurofeedback sessions (one-week apart practicing down-regulation of the amygdala-EFP signal. In the first session, half trained via the animated scenario and half via a thermometer interface. Learning efficiency was tested by three parameters: (a effect-size of the change in amygdala-EFP following training, (b sustainability of the learned down-regulation in the absence of online feedback, and (c transferability to an unfamiliar context. Comparing amygdala-EFP signal amplitude between the last and the first neurofeedback trials revealed that the animated scenario

Savage Vernacular: Performing Race, Memory, and Hip Hop in Filipino America

OpenAIRE

Villegas, Mark

2015-01-01

By observing and analyzing live performances, music, visual art, interviews, television shows, and online discourse, this dissertation traces the ways in which Filipino American hip hop performance remembers the racialized histories of the Filipino body. Through both quotidian and spectacular performances in hip hop, Filipino Americans have been contributing to crucial forms of knowledge that help unpack the terms of Filipino and American culture. Hip hop culture, I argue, operates as a produ...

"Deeper than Rap": Gifted Males and Their Relationship with Hip Hop Culture

Science.gov (United States)

Callahan, J. Sean; Grantham, Tarek C.

2012-01-01

One would be hard-pressed to deny the impact that hip hop is having on gifted students. More specifically, because hip hop is a creative and exciting male-dominated culture, gifted males gravitate to hip hop culture. From the perspective of two Black men from two different generations, this article was inspired by discussions about the role of hip…

Surface EMG signals based motion intent recognition using multi-layer ELM

Science.gov (United States)

Wang, Jianhui; Qi, Lin; Wang, Xiao

2017-11-01

The upper-limb rehabilitation robot is regard as a useful tool to help patients with hemiplegic to do repetitive exercise. The surface electromyography (sEMG) contains motion information as the electric signals are generated and related to nerve-muscle motion. These sEMG signals, representing human's intentions of active motions, are introduced into the rehabilitation robot system to recognize upper-limb movements. Traditionally, the feature extraction is an indispensable part of drawing significant information from original signals, which is a tedious task requiring rich and related experience. This paper employs a deep learning scheme to extract the internal features of the sEMG signals using an advanced Extreme Learning Machine based auto-encoder (ELMAE). The mathematical information contained in the multi-layer structure of the ELM-AE is used as the high-level representation of the internal features of the sEMG signals, and thus a simple ELM can post-process the extracted features, formulating the entire multi-layer ELM (ML-ELM) algorithm. The method is employed for the sEMG based neural intentions recognition afterwards. The case studies show the adopted deep learning algorithm (ELM-AE) is capable of yielding higher classification accuracy compared to the Principle Component Analysis (PCA) scheme in 5 different types of upper-limb motions. This indicates the effectiveness and the learning capability of the ML-ELM in such motion intent recognition applications.

Piezo activated mode tracking system for widely tunable mode-hop-free external cavity mid-IR semiconductor lasers

Science.gov (United States)

Wysocki, Gerard (Inventor); Tittel, Frank K. (Inventor); Curl, Robert F. (Inventor)

2010-01-01

A widely tunable, mode-hop-free semiconductor laser operating in the mid-IR comprises a QCL laser chip having an effective QCL cavity length, a diffraction grating defining a grating angle and an external cavity length with respect to said chip, and means for controlling the QCL cavity length, the external cavity length, and the grating angle. The laser of claim 1 wherein said chip may be tuned over a range of frequencies even in the absence of an anti-reflective coating. The diffraction grating is controllably pivotable and translatable relative to said chip and the effective QCL cavity length can be adjusted by varying the injection current to the chip. The laser can be used for high resolution spectroscopic applications and multi species trace-gas detection. Mode-hopping is avoided by controlling the effective QCL cavity length, the external cavity length, and the grating angle so as to replicate a virtual pivot point.

Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine

Science.gov (United States)

Maimaitijiang, Maitiniyazi; Ghulam, Abduwasit; Sidike, Paheding; Hartling, Sean; Maimaitiyiming, Matthew; Peterson, Kyle; Shavers, Ethan; Fishman, Jack; Peterson, Jim; Kadam, Suhas; Burken, Joel; Fritschi, Felix

2017-12-01

Estimating crop biophysical and biochemical parameters with high accuracy at low-cost is imperative for high-throughput phenotyping in precision agriculture. Although fusion of data from multiple sensors is a common application in remote sensing, less is known on the contribution of low-cost RGB, multispectral and thermal sensors to rapid crop phenotyping. This is due to the fact that (1) simultaneous collection of multi-sensor data using satellites are rare and (2) multi-sensor data collected during a single flight have not been accessible until recent developments in Unmanned Aerial Systems (UASs) and UAS-friendly sensors that allow efficient information fusion. The objective of this study was to evaluate the power of high spatial resolution RGB, multispectral and thermal data fusion to estimate soybean (Glycine max) biochemical parameters including chlorophyll content and nitrogen concentration, and biophysical parameters including Leaf Area Index (LAI), above ground fresh and dry biomass. Multiple low-cost sensors integrated on UASs were used to collect RGB, multispectral, and thermal images throughout the growing season at a site established near Columbia, Missouri, USA. From these images, vegetation indices were extracted, a Crop Surface Model (CSM) was advanced, and a model to extract the vegetation fraction was developed. Then, spectral indices/features were combined to model and predict crop biophysical and biochemical parameters using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Extreme Learning Machine based Regression (ELR) techniques. Results showed that: (1) For biochemical variable estimation, multispectral and thermal data fusion provided the best estimate for nitrogen concentration and chlorophyll (Chl) a content (RMSE of 9.9% and 17.1%, respectively) and RGB color information based indices and multispectral data fusion exhibited the largest RMSE 22.6%; the highest accuracy for Chl a + b content estimation was

Being Hipped to Their Hop: Tapping into Young Minds through Hip Hop Play

Science.gov (United States)

Broughton, Anthony

2017-01-01

Adults gain a wealth of knowledge from listening to the voices of children through intentional observations and interactions [Owocki, G., and Y. M. Goodman. 2002. "Kidwatching: Documenting Children's Literacy Development." Portsmouth: Heinemann]. Hip Hop play may provide optimal opportunities for teachers to tap into the young minds of…

Determination of the Geographical and Botanical Origin of Hops (Humulus lupulus L.) Using Stable Isotopes of C, N, and S.

Science.gov (United States)

Ocvirk, Miha; Ogrinc, Nives; Košir, Iztok Jože

2018-02-28

A need exists for a reliable method to determine the geographical and botanical origin of hops. For this study, three sets of samples were collected: the first set comprised 5 German samples; the second set comprised samples of hops from 10 of the world's major hop-growing regions; and the third comprised the 4 main Slovenian regions. The samples were analyzed using isotope ratio mass spectrometry (IRMS) to obtain δ 13 C, δ 15 N, and δ 34 S values. The δ 15 N (2.2 ‰ to 8.4 ‰) and δ 34 S (0.7 ‰ to 12.3 ‰) values were the most discriminating parameters for classifying hop according to geographical origin. ANOVA showed distinct groupings for 8 out of the 10 hop-growing regions. Although it was not possible to distinguish the geographical origin of hops based on δ 13 C (-28.9 ‰ to -24.7 ‰), in the case of botanical origin, δ 13 C values proved to be the most discriminative albeit with limited success.

Starting with Style: Toward a Second Wave of Hip-Hop Education Research and Practice

Science.gov (United States)

Petchauer, Emery

2015-01-01

One fundamental breakthrough in the field of hip-hop education in recent years is the shift from understanding hip-hop solely as content to understanding hip-hop also as aesthetic form. In this article, I chart the roots of this shift across disciplines and focus on what it might mean for the future of hip-hop education, pedagogy, and research in…

Hop powdery mildew control through alteration of spring pruning practices

Science.gov (United States)

Since 1997, Podosphaera macularis, the causal agent of hop powdery mildew, has become a recurrent threat to hops in the Pacific Northwest because of the potential to reduce cone yield and quality. Disease management practices often involve preventative fungicide applications, but alternative approac...

Hip-Hop, the "Obama Effect," and Urban Science Education

Science.gov (United States)

Emdin, Christopher; Lee, Okhee

2012-01-01

Background/Context: With the ever increasing diversity of schools, and the persistent need to develop teaching strategies for the students who attend today's urban schools, hip-hop culture has been proposed to be a means through which urban youth can find success in school. As a result, studies of the role of hip-hop in urban education have grown…

Hip Hop as Empowerment: Voices in El Alto, Bolivia

Science.gov (United States)

Tarifa, Ariana

2012-01-01

In response to neoliberal policies that have been in place since 1985, Bolivian young people have increasingly used hip hop music as a means of protest and to reclaim social and political participation. Hip hop in Latin America tells the story of the struggles that marginalized people have suffered, and speaks to the effects of international…

Muddy Learning: Evaluating Learning in Multi-User Computer-Based Environments

National Research Council Canada - National Science Library

McArthur, David

1998-01-01

... (Multiple User Synthetic Environments), and MOOs (Multi-User Object Oriented), enables users to create new "rooms" in virtual worlds, define their own personnaes, and engage visitors in rich dialogues...

Influence of Coherent Tunneling and Incoherent Hopping on the Charge Transfer Mechanism in Linear Donor-Bridge-Acceptor Systems.

Science.gov (United States)

Li, Guangqi; Govind, Niranjan; Ratner, Mark A; Cramer, Christopher J; Gagliardi, Laura

2015-12-17

The mechanism of charge transfer has been observed to change from tunneling to hopping with increasing numbers of DNA base pairs in polynucleotides and with the length of molecular wires. The aim of this paper is to investigate this transition by examining the population dynamics using a tight-binding Hamiltonian with model parameters to describe a linear donor-bridge-acceptor (D-B-A) system. The model includes a primary vibration and an electron-vibration coupling at each site. A further coupling of the primary vibration with a secondary phonon bath allows the system to dissipate energy to the environment and reach a steady state. We apply the quantum master equation (QME) approach, based on second-order perturbation theory in a quantum dissipative system, to examine the dynamical processes involved in charge-transfer and follow the population transfer rate at the acceptor, ka, to shed light on the transition from tunneling to hopping. With a small tunneling parameter, V, the on-site population tends to localize and form polarons, and the hopping mechanism dominates the transfer process. With increasing V, the population tends to be delocalized and the tunneling mechanism dominates. The competition between incoherent hopping and coherent tunneling governs the mechanism of charge transfer. By varying V and the total number of sites, we also examine the onset of the transition from tunneling to hopping with increasing length.

Influence of learning strategy on response time during complex value-based learning and choice.

Directory of Open Access Journals (Sweden)

Shiva Farashahi

Full Text Available Measurements of response time (RT have long been used to infer neural processes underlying various cognitive functions such as working memory, attention, and decision making. However, it is currently unknown if RT is also informative about various stages of value-based choice, particularly how reward values are constructed. To investigate these questions, we analyzed the pattern of RT during a set of multi-dimensional learning and decision-making tasks that can prompt subjects to adopt different learning strategies. In our experiments, subjects could use reward feedback to directly learn reward values associated with possible choice options (object-based learning. Alternatively, they could learn reward values of options' features (e.g. color, shape and combine these values to estimate reward values for individual options (feature-based learning. We found that RT was slower when the difference between subjects' estimates of reward probabilities for the two alternative objects on a given trial was smaller. Moreover, RT was overall faster when the preceding trial was rewarded or when the previously selected object was present. These effects, however, were mediated by an interaction between these factors such that subjects were faster when the previously selected object was present rather than absent but only after unrewarded trials. Finally, RT reflected the learning strategy (i.e. object-based or feature-based approach adopted by the subject on a trial-by-trial basis, indicating an overall faster construction of reward value and/or value comparison during object-based learning. Altogether, these results demonstrate that the pattern of RT can be informative about how reward values are learned and constructed during complex value-based learning and decision making.

Evaluation of airborne methyl salicylate for improved conservation biological control of two-spotted spider mite and hop aphid in Oregon hop yards.

Science.gov (United States)

Woods, J L; James, D G; Lee, J C; Gent, D H

2011-12-01

The use of synthetic herbivore-induced plant volatiles (HIPV) to attract natural enemies has received interest as a tool to enhance conservation biological control (CBC). Methyl salicylate (MeSA) is a HIPV that is attractive to several key predators of two-spotted spider mite, Tetranychus urticae Koch (Acari: Tetranychidae), and hop aphid, Phorodon humuli (Schrank) (Homoptera: Aphididae). A 2-year study was conducted to evaluate the recommended commercial use of MeSA in hop yards in Oregon. Slow-release MeSA dispensers were stapled to supporting poles in 0.5 ha plots and these plots were compared to a paired non-treated plot on each of three farms in 2008 and 2009. Across both years, there was a trend for reduced (range 40-91%) mean seasonal numbers of T. urticae in five of the six MeSA-baited plots. Stethorus spp., key spider mite predators, tended to be more numerous in MeSA-baited plots compared to control plots on a given farm. Mean seasonal densities of hop aphid and other natural enemies (e.g., Orius spp. and Anystis spp.) were similar between MeSA-treated and control plots. Variability among farms in suppression of two-spotted spider mites and attraction of Stethorus spp. suggests that the use of MeSA to enhance CBC of spider mites in commercial hop yards may be influenced by site-specific factors related to the agroecology of individual farms or seasonal effects that require further investigation. The current study also suggests that CBC of hop aphid with MeSA in this environment may be unsatisfactory.

Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning.

Science.gov (United States)

Huang, Chang-Qin; Yang, Shang-Ming; Pan, Yan; Lai, Han-Jiang

2018-09-01

Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary "mask" map that can identify the approximate locations of objects in an image, so that we use this binary "mask" map to obtain length-limited hash codes which mainly focus on an image's objects but ignore the background. The proposed deep architecture consists of four parts: 1) a convolutional sub-network to generate effective image features; 2) a binary "mask" sub-network to identify image objects' approximate locations; 3) a weighted average pooling operation based on the binary "mask" to obtain feature representations and hash codes that pay most attention to foreground objects but ignore the background; and 4) the combination of a triplet ranking loss designed to preserve relative similarities among images and a cross entropy loss defined on image labels. We conduct comprehensive evaluations on four multi-label image data sets. The results indicate that the proposed hashing method achieves superior performance gains over the state-of-the-art supervised or unsupervised hashing baselines.

Detect-and-forward in two-hop relay channels: a metrics-based analysis

KAUST Repository

Benjillali, Mustapha

2010-06-01

In this paper, we analyze the coded performance of a cooperative system with multiple parallel relays using "Detect-and-Forward" (DetF) strategy where each relay demodulates the overheard signal and forwards the detected binary words. The proposed method is based on the probabilistic characterization of the reliability metrics given under the form of L-values. First, we derive analytical expressions of the probability density functions (PDFs) of the L-values in the elementary two-hop DetF relay channel with different source-relay channel state information assumptions. Then, we apply the obtained expressions to calculate the theoretically achievable rates and compare them with the practical throughput of a simulated turbo-coded transmission. Next, we derive tight approximations for the end-to-end coded bit error rate (BER) of a general cooperative scheme with multiple parallel relays. Simulation results demonstrate the accuracy of our derivations for different cooperation configurations and conditions. © 2010 IEEE.

Linking the mechanics and energetics of hopping with elastic ankle exoskeletons.

Science.gov (United States)

Farris, Dominic James; Sawicki, Gregory S

2012-12-15

The springlike mechanics of the human leg during bouncing gaits has inspired the design of passive assistive devices that use springs to aid locomotion. The purpose of this study was to test whether a passive spring-loaded ankle exoskeleton could reduce the mechanical and energetic demands of bilateral hopping on the musculoskeletal system. Joint level kinematics and kinetics were collected with electromyographic and metabolic energy consumption data for seven participants hopping at four frequencies (2.2, 2.5, 2.8, and 3.2 Hz). Hopping was performed without an exoskeleton; with an springless exoskeleton; and with a spring-loaded exoskeleton. Spring-loaded ankle exoskeletons reduced plantar flexor muscle activity and the biological contribution to ankle joint moment (15-25%) and average positive power (20-40%). They also facilitated reductions in metabolic power (15-20%) across frequencies from 2.2 to 2.8 Hz compared with hopping with a springless exoskeleton. Reductions in metabolic power compared with hopping with no exoskeleton were restricted to hopping at 2.5 Hz only (12%). These results highlighted the importance of reducing the rate of muscular force production and work to achieve metabolic reductions. They also highlighted the importance of assisting muscles acting at the knee joint. Exoskeleton designs may need to be tuned to optimize exoskeleton mass, spring stiffness, and spring slack length to achieve greater metabolic reductions.

Design and performance analysis for several new classes of codes for optical synchronous CDMA and for arbitrary-medium time-hopping synchronous CDMA communication systems

Science.gov (United States)

Kostic, Zoran; Titlebaum, Edward L.

1994-08-01

New families of spread-spectrum codes are constructed, that are applicable to optical synchronous code-division multiple-access (CDMA) communications as well as to arbitrary-medium time-hopping synchronous CDMA communications. Proposed constructions are based on the mappings from integer sequences into binary sequences. We use the concept of number theoretic quadratic congruences and a subset of Reed-Solomon codes similar to the one utilized in the Welch-Costas frequency-hop (FH) patterns. The properties of the codes are as good as or better than the properties of existing codes for synchronous CDMA communications: Both the number of code-sequences within a single code family and the number of code families with good properties are significantly increased when compared to the known code designs. Possible applications are presented. To evaluate the performance of the proposed codes, a new class of hit arrays called cyclical hit arrays is recalled, which give insight into the previously unknown properties of the few classes of number theoretic FH patterns. Cyclical hit arrays and the proposed mappings are used to determine the exact probability distribution functions of random variables that represent interference between users of a time-hopping or optical CDMA system. Expressions for the bit error probability in multi-user CDMA systems are derived as a function of the number of simultaneous CDMA system users, the length of signature sequences and the threshold of a matched filter detector. The performance results are compared with the results for some previously known codes.

Behind Beats and Rhymes: Working Class from a Hampton Roads Hip Hop Homeplace

Science.gov (United States)

Durham, Aisha S.

2009-01-01

The film documentary titled "Hip Hop: beyond beats and rhymes" captures ongoing conversations among scholars, cultural critics, and hip hop insiders about the state of African Americans by interrogating distinct expressive forms associated with hip hop culture. Durham draws from two scenes to describe her memories as the researched…

Wish to Live: The Hip-Hop Feminism Pedagogy Reader. Educational Psychology. Volume 3

Science.gov (United States)

Brown, Ruth Nicole, Ed.; Kwakye, Chamara Jewel, Ed.

2012-01-01

"Wish To Live: The Hip-hop Feminism Pedagogy Reader" moves beyond the traditional understanding of the four elements of hip-hop culture--rapping, breakdancing, graffiti art, and deejaying--to articulate how hip-hop feminist scholarship can inform educational practices and spark, transform, encourage, and sustain local and global youth…

Enabling multi-level relevance feedback on PubMed by integrating rank learning into DBMS.

Science.gov (United States)

Yu, Hwanjo; Kim, Taehoon; Oh, Jinoh; Ko, Ilhwan; Kim, Sungchul; Han, Wook-Shin

2010-04-16

Finding relevant articles from PubMed is challenging because it is hard to express the user's specific intention in the given query interface, and a keyword query typically retrieves a large number of results. Researchers have applied machine learning techniques to find relevant articles by ranking the articles according to the learned relevance function. However, the process of learning and ranking is usually done offline without integrated with the keyword queries, and the users have to provide a large amount of training documents to get a reasonable learning accuracy. This paper proposes a novel multi-level relevance feedback system for PubMed, called RefMed, which supports both ad-hoc keyword queries and a multi-level relevance feedback in real time on PubMed. RefMed supports a multi-level relevance feedback by using the RankSVM as the learning method, and thus it achieves higher accuracy with less feedback. RefMed "tightly" integrates the RankSVM into RDBMS to support both keyword queries and the multi-level relevance feedback in real time; the tight coupling of the RankSVM and DBMS substantially improves the processing time. An efficient parameter selection method for the RankSVM is also proposed, which tunes the RankSVM parameter without performing validation. Thereby, RefMed achieves a high learning accuracy in real time without performing a validation process. RefMed is accessible at http://dm.postech.ac.kr/refmed. RefMed is the first multi-level relevance feedback system for PubMed, which achieves a high accuracy with less feedback. It effectively learns an accurate relevance function from the user's feedback and efficiently processes the function to return relevant articles in real time.

Representational Learning for Fault Diagnosis of Wind Turbine Equipment: A Multi-Layered Extreme Learning Machines Approach

Directory of Open Access Journals (Sweden)

Zhi-Xin Yang

2016-05-01

Full Text Available Reliable and quick response fault diagnosis is crucial for the wind turbine generator system (WTGS to avoid unplanned interruption and to reduce the maintenance cost. However, the conditional data generated from WTGS operating in a tough environment is always dynamical and high-dimensional. To address these challenges, we propose a new fault diagnosis scheme which is composed of multiple extreme learning machines (ELM in a hierarchical structure, where a forwarding list of ELM layers is concatenated and each of them is processed independently for its corresponding role. The framework enables both representational feature learning and fault classification. The multi-layered ELM based representational learning covers functions including data preprocessing, feature extraction and dimension reduction. An ELM based autoencoder is trained to generate a hidden layer output weight matrix, which is then used to transform the input dataset into a new feature representation. Compared with the traditional feature extraction methods which may empirically wipe off some “insignificant’ feature information that in fact conveys certain undiscovered important knowledge, the introduced representational learning method could overcome the loss of information content. The computed output weight matrix projects the high dimensional input vector into a compressed and orthogonally weighted distribution. The last single layer of ELM is applied for fault classification. Unlike the greedy layer wise learning method adopted in back propagation based deep learning (DL, the proposed framework does not need iterative fine-tuning of parameters. To evaluate its experimental performance, comparison tests are carried out on a wind turbine generator simulator. The results show that the proposed diagnostic framework achieves the best performance among the compared approaches in terms of accuracy and efficiency in multiple faults detection of wind turbines.

An Interactive Tool for Creating Multi-Agent Systems and Interactive Agent-based Games

DEFF Research Database (Denmark)

Lund, Henrik Hautop; Pagliarini, Luigi

2011-01-01

Utilizing principles from parallel and distributed processing combined with inspiration from modular robotics, we developed the modular interactive tiles. As an educational tool, the modular interactive tiles facilitate the learning of multi-agent systems and interactive agent-based games...

Learning from induced changes in opponent (re)actions in multi-agent games

NARCIS (Netherlands)

P.J. 't Hoen (Pieter Jan); S.M. Bohte (Sander); J.A. La Poutré (Han)

2005-01-01

textabstractMulti-agent learning is a growing area of research. An important topic is to formulate how an agent can learn a good policy in the face of adaptive, competitive opponents. Most research has focused on extensions of single agent learning techniques originally designed for agents in more

Sensor-Motor Maps for Describing Linear Reflex Composition in Hopping

Directory of Open Access Journals (Sweden)

Christian Schumacher

2017-11-01

Full Text Available In human and animal motor control several sensory organs contribute to a network of sensory pathways modulating the motion depending on the task and the phase of execution to generate daily motor tasks such as locomotion. To better understand the individual and joint contribution of reflex pathways in locomotor tasks, we developed a neuromuscular model that describes hopping movements. In this model, we consider the influence of proprioceptive length (LFB, velocity (VFB and force feedback (FFB pathways of a leg extensor muscle on hopping stability, performance and efficiency (metabolic effort. Therefore, we explore the space describing the blending of the monosynaptic reflex pathway gains. We call this reflex parameter space a sensor-motor map. The sensor-motor maps are used to visualize the functional contribution of sensory pathways in multisensory integration. We further evaluate the robustness of these sensor-motor maps to changes in tendon elasticity, body mass, segment length and ground compliance. The model predicted that different reflex pathway compositions selectively optimize specific hopping characteristics (e.g., performance and efficiency. Both FFB and LFB were pathways that enable hopping. FFB resulted in the largest hopping heights, LFB enhanced hopping efficiency and VFB had the ability to disable hopping. For the tested case, the topology of the sensor-motor maps as well as the location of functionally optimal compositions were invariant to changes in system designs (tendon elasticity, body mass, segment length or environmental parameters (ground compliance. Our results indicate that different feedback pathway compositions may serve different functional roles. The topology of the sensor-motor map was predicted to be robust against changes in the mechanical system design indicating that the reflex system can use different morphological designs, which does not apply for most robotic systems (for which the control often follows a

Sensor-Motor Maps for Describing Linear Reflex Composition in Hopping.

Science.gov (United States)

Schumacher, Christian; Seyfarth, André

2017-01-01

In human and animal motor control several sensory organs contribute to a network of sensory pathways modulating the motion depending on the task and the phase of execution to generate daily motor tasks such as locomotion. To better understand the individual and joint contribution of reflex pathways in locomotor tasks, we developed a neuromuscular model that describes hopping movements. In this model, we consider the influence of proprioceptive length (LFB), velocity (VFB) and force feedback (FFB) pathways of a leg extensor muscle on hopping stability, performance and efficiency (metabolic effort). Therefore, we explore the space describing the blending of the monosynaptic reflex pathway gains. We call this reflex parameter space a sensor-motor map . The sensor-motor maps are used to visualize the functional contribution of sensory pathways in multisensory integration. We further evaluate the robustness of these sensor-motor maps to changes in tendon elasticity, body mass, segment length and ground compliance. The model predicted that different reflex pathway compositions selectively optimize specific hopping characteristics (e.g., performance and efficiency). Both FFB and LFB were pathways that enable hopping. FFB resulted in the largest hopping heights, LFB enhanced hopping efficiency and VFB had the ability to disable hopping. For the tested case, the topology of the sensor-motor maps as well as the location of functionally optimal compositions were invariant to changes in system designs (tendon elasticity, body mass, segment length) or environmental parameters (ground compliance). Our results indicate that different feedback pathway compositions may serve different functional roles. The topology of the sensor-motor map was predicted to be robust against changes in the mechanical system design indicating that the reflex system can use different morphological designs, which does not apply for most robotic systems (for which the control often follows a specific

A Spatiotemporal Multi-View-Based Learning Method for Short-Term Traffic Forecasting

Directory of Open Access Journals (Sweden)

Shifen Cheng

2018-06-01

Full Text Available Short-term traffic forecasting plays an important part in intelligent transportation systems. Spatiotemporal k-nearest neighbor models (ST-KNNs have been widely adopted for short-term traffic forecasting in which spatiotemporal matrices are constructed to describe traffic conditions. The performance of the models is closely related to the spatial dependencies, the temporal dependencies, and the interaction of spatiotemporal dependencies. However, these models use distance functions and correlation coefficients to identify spatial neighbors and measure the temporal interaction by only considering the temporal closeness of traffic, which result in existing ST-KNNs that cannot fully reflect the essential features of road traffic. This study proposes an improved spatiotemporal k-nearest neighbor model for short-term traffic forecasting by utilizing a multi-view learning algorithm named MVL-STKNN that fully considers the spatiotemporal dependencies of traffic data. First, the spatial neighbors for each road segment are automatically determined using cross-correlation under different temporal dependencies. Three spatiotemporal views are built on the constructed spatiotemporal closeness, periodic, and trend matrices to represent spatially heterogeneous traffic states. Second, a spatiotemporal weighting matrix is introduced into the ST-KNN model to recognize similar traffic patterns in the three spatiotemporal views. Finally, the results of traffic pattern recognition under these three spatiotemporal views are aggregated by using a neural network algorithm to describe the interaction of spatiotemporal dependencies. Extensive experiments were conducted using real vehicular-speed datasets collected on city roads and expressways. In comparison with baseline methods, the results show that the MVL-STKNN model greatly improves short-term traffic forecasting by lowering the mean absolute percentage error between 28.24% and 46.86% for the city road dataset and

Optimal control in microgrid using multi-agent reinforcement learning.

Science.gov (United States)

Li, Fu-Dong; Wu, Min; He, Yong; Chen, Xin

2012-11-01

This paper presents an improved reinforcement learning method to minimize electricity costs on the premise of satisfying the power balance and generation limit of units in a microgrid with grid-connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of optimal control for microgrid is proposed. Then, a state variable "Average Electricity Price Trend" which is used to express the most possible transitions of the system is developed so as to reduce the complexity and randomicity of the microgrid, and a multi-agent architecture including agents, state variables, action variables and reward function is formulated. Furthermore, dynamic hierarchical reinforcement learning, based on change rate of key state variable, is established to carry out optimal policy exploration. The analysis shows that the proposed method is beneficial to handle the problem of "curse of dimensionality" and speed up learning in the unknown large-scale world. Finally, the simulation results under JADE (Java Agent Development Framework) demonstrate the validity of the presented method in optimal control for a microgrid with grid-connected mode. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

A novel multi-agent decentralized win or learn fast policy hill-climbing with eligibility trace algorithm for smart generation control of interconnected complex power grids

International Nuclear Information System (INIS)

Xi, Lei; Yu, Tao; Yang, Bo; Zhang, Xiaoshun

2015-01-01

Highlights: • Proposing a decentralized smart generation control scheme for the automatic generation control coordination. • A novel multi-agent learning algorithm is developed to resolve stochastic control problems in power systems. • A variable learning rate are introduced base on the framework of stochastic games. • A simulation platform is developed to test the performance of different algorithms. - Abstract: This paper proposes a multi-agent smart generation control scheme for the automatic generation control coordination in interconnected complex power systems. A novel multi-agent decentralized win or learn fast policy hill-climbing with eligibility trace algorithm is developed, which can effectively identify the optimal average policies via a variable learning rate under various operation conditions. Based on control performance standards, the proposed approach is implemented in a flexible multi-agent stochastic dynamic game-based smart generation control simulation platform. Based on the mixed strategy and average policy, it is highly adaptive in stochastic non-Markov environments and large time-delay systems, which can fulfill automatic generation control coordination in interconnected complex power systems in the presence of increasing penetration of decentralized renewable energy. Two case studies on both a two-area load–frequency control power system and the China Southern Power Grid model have been done. Simulation results verify that multi-agent smart generation control scheme based on the proposed approach can obtain optimal average policies thus improve the closed-loop system performances, and can achieve a fast convergence rate with significant robustness compared with other methods

The Effect of Rap/Hip-Hop Music on Young Adult Smoking: An Experimental Study.

Science.gov (United States)

Harakeh, Zeena; Bogt, Tom F M Ter

2018-02-16

Music may influence young people's behavior through its lyrics. Substance use references occur more frequently in rap/hip-hop than in other music genres. The aim was to examine whether the exposure to rap/hip-hop lyrics referring to substance use affected cigarette smoking. An experiment with a 3-group between subject design was conducted among 74 daily-smoking young adults ranging in age from 17 to 25 years old. Three conditions were tested in a mobile lab (camper vehicle) from May to December 2011, i.e., regular chart pop music (N = 28), rap/hip-hop with non-frequent references to substance use (N = 24), and rap/hip-hop with frequent references to substance use (N = 22). One-way ANOVA showed that participants listening to substance use infused rap/hip-hop songs felt significantly less pleasant, liked the songs less, and comprehended the songs less compared to participants listening to pop songs. Poisson loglinear analyses revealed that compared to the pop music condition, none of the two rap/hip-hop music conditions had a significant effect on acute smoking. Thus, contrary to expectations, the two different rap/hip-hop conditions did not have a significantly different effect on acute smoking. Listening to rap/hip-hop, even rap hip/hop with frequent referrals to substance use (primarily alcohol and drug use, and general smoking referrals), does not seem to encourage cigarette smoking among Dutch daily-smoking young adults, at least short term.

Range and energetics of charge hopping in organic semiconductors

Science.gov (United States)

Abdalla, Hassan; Zuo, Guangzheng; Kemerink, Martijn

2017-12-01

The recent upswing in attention for the thermoelectric properties of organic semiconductors (OSCs) adds urgency to the need for a quantitative description of the range and energetics of hopping transport in organic semiconductors under relevant circumstances, i.e., around room temperature (RT). In particular, the degree to which hops beyond the nearest neighbor must be accounted for at RT is still largely unknown. Here, measurements of charge and energy transport in doped OSCs are combined with analytical modeling to reach the univocal conclusion that variable-range hopping is the proper description in a large class of disordered OSC at RT. To obtain quantitative agreement with experiment, one needs to account for the modification of the density of states by ionized dopants. These Coulomb interactions give rise to a deep tail of trap states that is independent of the material's initial energetic disorder. Insertion of this effect into a classical Mott-type variable-range hopping model allows one to give a quantitative description of temperature-dependent conductivity and thermopower measurements on a wide range of disordered OSCs. In particular, the model explains the commonly observed quasiuniversal power-law relation between the Seebeck coefficient and the conductivity.

Uudised : Ooper. Hip-hop. Madonna

Index Scriptorium Estoniae

2005-01-01

Rumeenia sopran Nelly Miricioiu Vincenzo Bellini ooperi "Norma" nimiosas Nederlandse Operas Amsaterdamis 7.-28. märtsini. 4. märtsil Tallinna klubis Hollywood üritusel "Hip-Hop Café" New Yorgi duo Camp Lo. Ameerika poplaulja Madonna võttis vastu filmirolli

Aero Engine Component Fault Diagnosis Using Multi-Hidden-Layer Extreme Learning Machine with Optimized Structure

Directory of Open Access Journals (Sweden)

Shan Pang

2016-01-01

Full Text Available A new aero gas turbine engine gas path component fault diagnosis method based on multi-hidden-layer extreme learning machine with optimized structure (OM-ELM was proposed. OM-ELM employs quantum-behaved particle swarm optimization to automatically obtain the optimal network structure according to both the root mean square error on training data set and the norm of output weights. The proposed method is applied to handwritten recognition data set and a gas turbine engine diagnostic application and is compared with basic ELM, multi-hidden-layer ELM, and two state-of-the-art deep learning algorithms: deep belief network and the stacked denoising autoencoder. Results show that, with optimized network structure, OM-ELM obtains better test accuracy in both applications and is more robust to sensor noise. Meanwhile it controls the model complexity and needs far less hidden nodes than multi-hidden-layer ELM, thus saving computer memory and making it more efficient to implement. All these advantages make our method an effective and reliable tool for engine component fault diagnosis tool.

Teaching Controversal Topics in Contemporary German Culture through Hip-Hop

Science.gov (United States)

Putnam, Michael

2006-01-01

This article discusses the rich cultural resources embedded with German hip-hop music and its potential impact on the foreign language classroom. In particular, this article suggests methods and materials for integrating German hip-hop music in the discussion of recent controversial cultural events and attitudes in German after the "Wende."

Membrane-bound ATPase contributes to hop resistance of Lactobacillus brevis

NARCIS (Netherlands)

Sakamoto, K; van Veen, HW; Saito, H; Kobayashi, H; Konings, WN

2002-01-01

The activity of the membrane-bound H+-ATPase of the beer spoilage bacterium Lactobacillus brevis ABBC45 increased upon adaptation to bacteriostatic hop compounds. The ATPase activity was optimal around pH 5.6 and increased up to fourfold when L. brevis was exposed to 666 muM hop compounds. The

Within-field distribution of the damson-hop aphid Phorodon humuli (Schrank) (Hemiptera: Aphididae) and natural enemies on hops in Spain

Energy Technology Data Exchange (ETDEWEB)

Lorenzana, A.; Hermoso de Mendoza, A.; Seco, V.; Campelo, P.; Casquero, P.A.

2017-07-01

A field trial was performed in a hop yard throughout 2002, 2003 and 2004 in order to determine the within-field distribution of Phorodon humuli (Schrank) (Hemiptera: Aphididae) and its natural enemies. The distribution of P. humuli was directly affected by the position of the hop plants in the garden, with significantly higher concentrations of aphids (p=0.0122 in 2002 and p=0.0006 in 2003) observed along the edge. However, in 2004 the plants located on the marginal plots had similar populations to those on the more inner plots. This can be explained by a higher wind speed which made it more difficult to land on edge plants first. The hop aphid’s main natural enemy was Coccinella septempunctata (Coleoptera: Coccinellidae), whose population was greatest where the aphids were most abundant with a significantly greater number of eggs (p=0.0230) and adults (p=0.0245) in 2003. Lacewing eggs were also frequently observed, with a significantly higher population (p=0.0221 in 2003 and p=0.0046 in 2004) where the aphid numbers were high. The number of winged aphids was greatest towards the margins of the garden in 2003. It is argued that the spatial distribution of the hop aphid and its natural enemies could be used to plan a sampling program and to estimate the population densities of these insects for use in integrated pest management programs.

Within-field distribution of the damson-hop aphid Phorodon humuli (Schrank) (Hemiptera: Aphididae) and natural enemies on hops in Spain

International Nuclear Information System (INIS)

Lorenzana, A.; Hermoso de Mendoza, A.; Seco, V.; Campelo, P.; Casquero, P.A.

2017-01-01

A field trial was performed in a hop yard throughout 2002, 2003 and 2004 in order to determine the within-field distribution of Phorodon humuli (Schrank) (Hemiptera: Aphididae) and its natural enemies. The distribution of P. humuli was directly affected by the position of the hop plants in the garden, with significantly higher concentrations of aphids (p=0.0122 in 2002 and p=0.0006 in 2003) observed along the edge. However, in 2004 the plants located on the marginal plots had similar populations to those on the more inner plots. This can be explained by a higher wind speed which made it more difficult to land on edge plants first. The hop aphid’s main natural enemy was Coccinella septempunctata (Coleoptera: Coccinellidae), whose population was greatest where the aphids were most abundant with a significantly greater number of eggs (p=0.0230) and adults (p=0.0245) in 2003. Lacewing eggs were also frequently observed, with a significantly higher population (p=0.0221 in 2003 and p=0.0046 in 2004) where the aphid numbers were high. The number of winged aphids was greatest towards the margins of the garden in 2003. It is argued that the spatial distribution of the hop aphid and its natural enemies could be used to plan a sampling program and to estimate the population densities of these insects for use in integrated pest management programs.

Multi-Destination Cognitive Radio Relay Network with SWIPT and Multiple Primary Receivers

KAUST Repository

Al-Habob, Ahmed A.; Salhab, Anas M.; Zummo, Salam A.; Alouini, Mohamed-Slim

2017-01-01

In this paper, we study the performance of simultaneous wireless information and power transfer (SWIPT) technique in a multi-destination dual-hop underlay cognitive relay network with multiple primary receivers. Information transmission from

Research on Improved DV-HOP Algorithm against Wormhole Attacks in WSN

Directory of Open Access Journals (Sweden)

Wang Xue-Wen

2016-01-01

Full Text Available The secure location of node is significant in the WSN (Wireless Sensor Networks of the troop frontier defence system. The wormhole attack is a big threat in the secure location. The credibility of the beacon node was used to determine the malicious nodes produced by wormhole attack in the WSN. The estimated method of multibeacon nodes was adopted to improve DV-HOP algorithm after excluding the malicious nodes. In this paper, we compared the basic DV-HOP algorithm and the improved DV-HOP algorithm in the coverage percentage and the error of network localization by simulating. The simulation results indicate that the improved DV-HOP algorithm makes the localization coverage percentage can reach 90% on a certain scale of the network, and it makes the error percentage lower when the number of beacons is different.

Affiliation and Alienation: Hip-Hop, Rap, and Urban Science Education

Science.gov (United States)

Emdin, Christopher

2010-01-01

The critiques of rap artists and other participants in hip-hop culture provide data for teachers and researchers to investigate the attitudes of US urban youth towards schooling. This study explores the complex relationships between hip-hop and science education by examining how rap lyrics project beliefs about schooling, the relevance of existing…

Hops (Humulus lupulus L. Bitter Acids: Modulation of Rumen Fermentation and Potential As an Alternative Growth Promoter

Directory of Open Access Journals (Sweden)

Michael D. Flythe

2017-08-01

Full Text Available Antibiotics can improve ruminant growth and efficiency by altering rumen fermentation via selective inhibition of microorganisms. However, antibiotic use is increasingly restricted due to concerns about the spread of antibiotic-resistance. Plant-based antimicrobials are alternatives to antibiotics in animal production. The hops plant (Humulus lupulus L. produces a range of bioactive secondary metabolites, including antimicrobial prenylated phloroglucinols, which are commonly called alpha- and beta-acids. These latter compounds can be considered phyto-ionophores, phytochemicals with a similar antimicrobial mechanism of action to ionophore antibiotics (e.g., monensin, lasalocid. Like ionophores, the hop beta-acids inhibit rumen bacteria possessing a classical Gram-positive cell envelope. This selective inhibition causes several effects on rumen fermentation that are beneficial to finishing cattle, such as decreased proteolysis, ammonia production, acetate: propionate ratio, and methane production. This article reviews the effects of hops and hop secondary metabolites on rumen fermentation, including the physiological mechanisms on specific rumen microorganisms, and consequences for the ruminant host and ruminant production. Further, we propose that hop beta-acids are useful model natural products for ruminants because of (1 the ionophore-like mechanism of action and spectrum of activity and (2 the literature available on the plant due to its use in brewing.

RNAi knockdown of Hop (Hsp70/Hsp90 organising protein) decreases invasion via MMP-2 down regulation.

LENUS (Irish Health Repository)

Walsh, Naomi

2011-07-28

We previously identified Hop as over expressed in invasive pancreatic cancer cell lines and malignant tissues of pancreatic cancer patients, suggesting an important role for Hop in the biology of invasive pancreatic cancer. Hop is a co-chaperone protein that binds to both Hsp70\\/Hsp90. We hypothesised that by targeting Hop, signalling pathways modulating invasion and client protein stabilisation involving Hsp90-dependent complexes may be altered. In this study, we show that Hop knockdown by small interfering (si)RNA reduces the invasion of pancreatic cancer cells, resulting in decreased expression of the downstream target gene, matrix metalloproteinases-2 (MMP-2). Hop in conditioned media co-immunoprecipitates with MMP-2, implicating a possible extracellular function for Hop. Knockdown of Hop expression also reduced expression levels of Hsp90 client proteins, HER2, Bcr-Abl, c-MET and v-Src. Furthermore, Hop is strongly expressed in high grade PanINs compared to lower PanIN grades, displaying differential localisation in invasive ductal pancreatic cancer, indicating that the localisation of Hop is an important factor in pancreatic tumours. Our data suggests that the attenuation of Hop expression inactivates key signal transduction proteins which may decrease the invasiveness of pancreatic cancer cells possibly through the modulation of Hsp90 activity. Therefore, targeting Hop in pancreatic cancer may constitute a viable strategy for targeted cancer therapy.

Post-Menopausal Vaginal Hemorrhage Related to the Use of a Hop-Containing Phytotherapeutic Product

NARCIS (Netherlands)

van Hunsel, Florence; van de Koppel, Sonja; van Puijenbroek, Eugène

2015-01-01

Two 54-year-old women developed abdominal cramps and vaginal hemorrhage as a result of endometrial hyperplasia during treatment with a hop-containing phytotherapeutic product (MenoCool®) for post-menopausal complaints. The women used the hop-containing phytotherapeutic product (418 mg of hop per

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

Science.gov (United States)

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database.

Science.gov (United States)

Choi, Joon Yul; Yoo, Tae Keun; Seo, Jeong Gi; Kwak, Jiyong; Um, Terry Taewoong; Rim, Tyler Hyungtaek

2017-01-01

Deep learning emerges as a powerful tool for analyzing medical images. Retinal disease detection by using computer-aided diagnosis from fundus image has emerged as a new method. We applied deep learning convolutional neural network by using MatConvNet for an automated detection of multiple retinal diseases with fundus photographs involved in STructured Analysis of the REtina (STARE) database. Dataset was built by expanding data on 10 categories, including normal retina and nine retinal diseases. The optimal outcomes were acquired by using a random forest transfer learning based on VGG-19 architecture. The classification results depended greatly on the number of categories. As the number of categories increased, the performance of deep learning models was diminished. When all 10 categories were included, we obtained results with an accuracy of 30.5%, relative classifier information (RCI) of 0.052, and Cohen's kappa of 0.224. Considering three integrated normal, background diabetic retinopathy, and dry age-related macular degeneration, the multi-categorical classifier showed accuracy of 72.8%, 0.283 RCI, and 0.577 kappa. In addition, several ensemble classifiers enhanced the multi-categorical classification performance. The transfer learning incorporated with ensemble classifier of clustering and voting approach presented the best performance with accuracy of 36.7%, 0.053 RCI, and 0.225 kappa in the 10 retinal diseases classification problem. First, due to the small size of datasets, the deep learning techniques in this study were ineffective to be applied in clinics where numerous patients suffering from various types of retinal disorders visit for diagnosis and treatment. Second, we found that the transfer learning incorporated with ensemble classifiers can improve the classification performance in order to detect multi-categorical retinal diseases. Further studies should confirm the effectiveness of algorithms with large datasets obtained from hospitals.

ADMultiImg: a novel missing modality transfer learning based CAD system for diagnosis of MCI due to AD using incomplete multi-modality imaging data

Science.gov (United States)

Liu, Xiaonan; Chen, Kewei; Wu, Teresa; Weidman, David; Lure, Fleming; Li, Jing

2018-02-01

Alzheimer's Disease (AD) is the most common cause of dementia and currently has no cure. Treatments targeting early stages of AD such as Mild Cognitive Impairment (MCI) may be most effective to deaccelerate AD, thus attracting increasing attention. However, MCI has substantial heterogeneity in that it can be caused by various underlying conditions, not only AD. To detect MCI due to AD, NIA-AA published updated consensus criteria in 2011, in which the use of multi-modality images was highlighted as one of the most promising methods. It is of great interest to develop a CAD system based on automatic, quantitative analysis of multi-modality images and machine learning algorithms to help physicians more adequately diagnose MCI due to AD. The challenge, however, is that multi-modality images are not universally available for many patients due to cost, access, safety, and lack of consent. We developed a novel Missing Modality Transfer Learning (MMTL) algorithm capable of utilizing whatever imaging modalities are available for an MCI patient to diagnose the patient's likelihood of MCI due to AD. Furthermore, we integrated MMTL with radiomics steps including image processing, feature extraction, and feature screening, and a post-processing for uncertainty quantification (UQ), and developed a CAD system called "ADMultiImg" to assist clinical diagnosis of MCI due to AD using multi-modality images together with patient demographic and genetic information. Tested on ADNI date, our system can generate a diagnosis with high accuracy even for patients with only partially available image modalities (AUC=0.94), and therefore may have broad clinical utility.

Towards a Pedagogy of Hip Hop in Urban Teacher Education

Science.gov (United States)

Bridges, Thurman

2011-01-01

This article draws from a qualitative study often Black male K-12 teachers from the Hip Hop Generation who are closely connected to Hip Hop culture and have been effective in addressing the academic and social needs of Black boys. Through an analysis of their social, educational and cultural experiences, this article highlights three organizing…

hMuLab: A Biomedical Hybrid MUlti-LABel Classifier Based on Multiple Linear Regression.

Science.gov (United States)

Wang, Pu; Ge, Ruiquan; Xiao, Xuan; Zhou, Manli; Zhou, Fengfeng

2017-01-01

Many biomedical classification problems are multi-label by nature, e.g., a gene involved in a variety of functions and a patient with multiple diseases. The majority of existing classification algorithms assumes each sample with only one class label, and the multi-label classification problem remains to be a challenge for biomedical researchers. This study proposes a novel multi-label learning algorithm, hMuLab, by integrating both feature-based and neighbor-based similarity scores. The multiple linear regression modeling techniques make hMuLab capable of producing multiple label assignments for a query sample. The comparison results over six commonly-used multi-label performance measurements suggest that hMuLab performs accurately and stably for the biomedical datasets, and may serve as a complement to the existing literature.

Robust visual tracking via structured multi-task sparse learning

KAUST Repository

Zhang, Tianzhu

2012-11-09

In this paper, we formulate object tracking in a particle filter framework as a structured multi-task sparse learning problem, which we denote as Structured Multi-Task Tracking (S-MTT). Since we model particles as linear combinations of dictionary templates that are updated dynamically, learning the representation of each particle is considered a single task in Multi-Task Tracking (MTT). By employing popular sparsity-inducing lp,q mixed norms (specifically p∈2,∞ and q=1), we regularize the representation problem to enforce joint sparsity and learn the particle representations together. As compared to previous methods that handle particles independently, our results demonstrate that mining the interdependencies between particles improves tracking performance and overall computational complexity. Interestingly, we show that the popular L1 tracker (Mei and Ling, IEEE Trans Pattern Anal Mach Intel 33(11):2259-2272, 2011) is a special case of our MTT formulation (denoted as the L11 tracker) when p=q=1. Under the MTT framework, some of the tasks (particle representations) are often more closely related and more likely to share common relevant covariates than other tasks. Therefore, we extend the MTT framework to take into account pairwise structural correlations between particles (e.g. spatial smoothness of representation) and denote the novel framework as S-MTT. The problem of learning the regularized sparse representation in MTT and S-MTT can be solved efficiently using an Accelerated Proximal Gradient (APG) method that yields a sequence of closed form updates. As such, S-MTT and MTT are computationally attractive. We test our proposed approach on challenging sequences involving heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that S-MTT is much better than MTT, and both methods consistently outperform state-of-the-art trackers. © 2012 Springer Science+Business Media New York.

Mood after various brief exercise and sport modes: aerobics, hip-hop dancing, ice skating, and body conditioning.