Do SMEs cluster around innovation activities? Discovering active, incremental and opportunistic innovators

Do SMEs cluster around different types of innovation activities? Are there patterns of SME innovation activities? To investigate we develop a taxonomy of innovation activities in SMEs using a qualitative study, followed by a survey. First, based upon our qualitative research and literature review we develop a comprehensive list of innovation activities SMEs typically engage in. We then conduct a factor analysis to determine if these activities can be combined into factors. We identify three innovation activity factors: R&D activities, incremental innovation activities and cost innovation activities. We use these factors to identify three clusters of firms engaging in similar innovation activities: active innovators, incremental innovators and opportunistic innovators. The clusters are enriched by validating that they also exhibit significant internal similarities and external differences in their innovation skills, demographics, industry segments and family business ownership. This research contributes to innovation and SME theory and practice by identifying SME clusters based upon their innovation activities.

OPSM - Opportunistic Power Save mode for Infrastructure IEEE 802.11 WLAN

We focus on the energy spent in radio communication by the stations (STAs) in an IEEE 802.11 infrastructure WLAN. All the STAs are engaged in web browsing, which is characterized by a short file downloads over TCP, with short duration of inactivity or think time in between two file downloads. Under this traffic, Static PSM (SPSM) performs better than CAM, since the STAs in SPSM can switch to low power state (sleep) during think times while in CAM they have to be in the active state all the time. In spite of this gain, performance of SPSM degrades due to congestion, as the number of STAs associated with the access point (AP) increases. To address this problem, we propose an algorithm, which we call opportunistic PSM (OPSM). We show through simulations that OPSM performs better than SPSM under the aforementioned TCP traffic. The performance gain achieved by OPSM over SPSM increases as the mean file size requested by the STAs or the number of STAs associated with the AP increases. We implemented OPSM in NS-2.33, and to compare the performance of OPSM and SPSM, we evaluate the number of file downloads that can be completed with a given battery capacity and the average time taken to download a file.

Providing quality of service via opportunistic splitting using stochastic approximation

We consider the problem of wireless channel allocation to multiple users. A slot is given to a user with a highest metric (e.g., channel gain) in that slot. The scheduler may not know the channel states of all the users at the beginning of each slot. In this scenario opportunistic splitting is an attractive solution. However this algorithm requires that the metrics of different users form independent, identically distributed (iid) sequences with same distribution and that their distribution and number be known to the scheduler. This limits the usefulness of opportunistic splitting. In this paper we develop a parametric version of this algorithm. The optimal parameters of the algorithm are learnt online through a stochastic approximation scheme. Our algorithm does not require the metrics of different users to have the same distribution. The statistics of these metrics and the number of users can be unknown and also vary with time. Each metric sequence can be Markov. We prove the convergence of the algorithm and show its utility by scheduling the channel to maximize its throughput while satisfying some fairness and/or quality of service constraints.

Opportunistic splitting for scheduling via stochastic approximation

We consider the problem of scheduling a wireless channel among multiple users. A slot is given to a user with a highest metric (e.g., channel gain) in that slot. The scheduler may not know the channel states of all the users at the beginning of each slot. In this scenario opportunistic splitting is an attractive solution. However this algorithm requires that the metrics of different users form independent, identically distributed (iid) sequences with same distribution and that their distribution and number be known to the scheduler. This limits the usefulness of opportunistic splitting. In this paper we develop a parametric version of this algorithm. The optimal parameters of the algorithm are learnt online through a stochastic approximation scheme. Our algorithm does not require the metrics of different users to have the same distribution. The statistics of these metrics and the number of users can be unknown and also vary with time. We prove the convergence of the algorithm and show its utility by scheduling the channel to maximize its throughput while satisfying some fairness and/or quality of service constraints.

Opportunistic scheduling of wireless links

We consider the problem of scheduling of a wireless channel (server) to several queues. Each queue has its own link (transmission) rate. The link rate of a queue can vary randomly from slot to slot. The queue lengths and channel states of all users are known at the beginning of each slot. We show the existence of an optimal policy that minimizes the long term (discounted) average sum of queue lengths. The optimal policy, in general needs to be computed numerically. Then we identify a greedy (one step optimal) policy, MAX-TRANS which is easy to implement and does not require the channel and traffic statistics. The cost of this policy is close to optimal and better than other well-known policies (when stable) although it is not throughput optimal for asymmetric systems. We (approximately) identify its stability region and obtain approximations for its mean queue lengths and mean delays. We also modify this policy to make it throughput optimal while retaining good performance.

Opportunistic Scheduling in Cellular Systems in the Presence of Noncooperative Mobiles

A central scheduling problem in wireless communications is that of allocating resources to one of many mobile stations that have a common radio channel. Much attention has been given to the design of efficient and fair scheduling schemes that are centrally controlled by a base station (BS) whose decisions depend on the channel conditions reported by each mobile. The BS is the only entity taking decisions in this framework. The decisions are based on the reports of mobiles on their radio channel conditions. In this paper, we study the scheduling problem from a game-theoretic perspective in which some of the mobiles may be noncooperative or strategic, and may not necessarily report their true channel conditions. We model this situation as a signaling game and study its equilibria. We demonstrate that the only Perfect Bayesian Equilibria (PBE) of the signaling game are of the babbling type: the noncooperative mobiles send signals independent of their channel states, the BS simply ignores them, and allocates channels based only on the prior information on the channel statistics. We then propose various approaches to enforce truthful signaling of the radio channel conditions: a pricing approach, an approach based on some knowledge of the mobiles' policies, and an approach that replaces this knowledge by a stochastic approximations approach that combines estimation and control. We further identify other equilibria that involve non-truthful signaling.

An Opportunistic, Fast, and Distributed Subchannel and User-Pairing Algorithm for OFDMA

Channel-aware assignment of subchannels to users in the downlink of an OFDMA system requires extensive feedback of channel state information (CSI) to the base station. Since bandwidth is scarce, schemes that limit feedback are necessary. We develop a novel, low feedback, distributed splitting-based algorithm called SplitSelect to opportunistically assign each subchannel to its most suitable user. SplitSelect explicitly handles multiple access control aspects associated with CSI feedback, and scales well with the number of users. In it, according to a scheduling criterion, each user locally maintains a scheduling metric for each subchannel. The goal is to select, for each subchannel, the user with the highest scheduling metric. At any time, each user contends for the subchannel for which it has the largest scheduling metric among the unallocated subchannels. A tractable asymptotic analysis of a system with many users is central to SplitSelect's simple design. Extensive simulation results demonstrate the speed with which subchannels and users are paired. The net data throughput, when the time overhead of selection is accounted for, is shown to be substantially better than several schemes proposed in the literature. We also show how fairness and user prioritization can be ensured by suitably defining the scheduling metric.

Accurate performance analysis of single and opportunistic AF relay cooperation with imperfect cascaded channel estimates

Given the significant gains that relay-based cooperation promises, the practical problems of acquisition of channel state information (CSI) and the characterization and optimization of performance with imperfect CSI are receiving increasing attention. We develop novel and accurate expressions for the symbol error probability (SEP) for fixed-gain amplify-and-forward relaying when the destination acquires CSI using the time-efficient cascaded channel estimation (CCE) protocol. The CCE protocol saves time by making the destination directly estimate the product of the source-relay and relay-destination channel gains. For a single relay system, we first develop a novel SEP expression and a tight SEP upper bound. We then similarly analyze an opportunistic multi-relay system, in which both selection and coherent demodulation use imperfect estimates. A distinctive aspect of our approach is the use of as few simplifying approximations as possible, which results in new results that are accurate at signal-to-noise-ratios as low as 1 dB for single and multi-relay systems. Using insights gleaned from an asymptotic analysis, we also present a simple, closed-form, nearly-optimal solution for allocation of energy between pilot and data symbols at the source and relay(s).

Interplay Between Optimal Selection Scheme, Selection Criterion, and Discrete Rate Adaptation in Opportunistic Wireless Systems

An opportunistic, rate-adaptive system exploits multi-user diversity by selecting the best node, which has the highest channel power gain, and adapting the data rate to selected node's channel gain. Since channel knowledge is local to a node, we propose using a distributed, low-feedback timer backoff scheme to select the best node. It uses a mapping that maps the channel gain, or, in general, a real-valued metric, to a timer value. The mapping is such that timers of nodes with higher metrics expire earlier. Our goal is to maximize the system throughput when rate adaptation is discrete, as is the case in practice. To improve throughput, we use a pragmatic selection policy, in which even a node other than the best node can be selected. We derive several novel, insightful results about the optimal mapping and develop an algorithm to compute it. These results bring out the inter-relationship between the discrete rate adaptation rule, optimal mapping, and selection policy. We also extensively benchmark the performance of the optimal mapping with several timer and opportunistic multiple access schemes considered in the literature, and demonstrate that the developed scheme is effective in many regimes of interest.

Co-Evolution of Content Spread and Popularity in Mobile Opportunistic Networks

We consider a setting in which a single item of content is disseminated in a population of mobile nodes by opportunistic copying when pairs of nodes come in radio contact. The nodes in the population may either be interested in receiving the content (referred to as destinations) or not yet interested in receiving the content (referred to as relays). We consider a model for the evolution of popularity, the process by which relays get converted into destinations. A key contribution of our work is to model and study the joint evolution of content popularity and its spread in the population. Copying the content to relay nodes is beneficial since they can help spread the content to destinations, and could themselves be converted into destinations. We derive a fluid limit for the joint evolution model and obtain optimal policies for copying to relay nodes in order to deliver content to a desired fraction of destinations, while limiting the fraction of relay nodes that get the content but never turn into destinations. We prove that a time-threshold policy is optimal for controlling the copying to relays, i.e., there is an optimal time-threshold up to which all opportunities for copying to relays are exploited, and after which relays are not copied to. We then utilize simulations and numerical evaluations to provide insights into the effects of various system parameters on the optimally controlled co-evolution model.

Harmful algal blooms in the PICES region of the North Pacific

Foreword Background and objectives [pdf, 0.84 MB] Country reviews and status reports Section I. Western North Pacific Japan Yasuwo Fukuyo, Ichiro Imai, Masaaki Kodama and Kyoichi Tamai Red tides and harmful algal blooms in Japan [pdf, 0.7 MB] People's Republic of China Tian Yan, Ming-Jiang Zhou and Jing-Zhong Zou A national report of HABs in China [pdf, 0.24 MB] Republic of Korea Sam Geun Lee, Hak Gyoon Kim, Eon Seob Cho and Chang Kyu Lee Harmful algal blooms (red tides): Management and mitigation in Korea [pdf, 0.27 MB] Russia Tatiana Y. Orlova, Galina V. Konovalova, Inna V. Stonik, Tatiana V. Morozova and Olga G. Shevchenko Harmful algal blooms on the eastern coast of Russia [pdf, 1.4 MB] Section II. Eastern North Pacific Canada F.J.R. "Max" Taylor and Paul J. Harrison Harmful marine algal blooms in western Canada [pdf, 0.87 MB] United States of America Vera L. Trainer Harmful algal blooms on the U.S. west coast [pdf, 0.5 MB] Mexico Jose L. Ochoa, S. Lluch-Cota, B.O. Arredondo-Vega, E. Nuñes-Vázquez, A. Heredia-Tapia, J. Pérez-Linares and R. Alonso-Rodriguez Marine Biotoxins and harmful algal blooms in Mexico's Pacific littora [pdf, 0.2 MB] Summary and conclusions [pdf, 0.6 MB] Appendices A. Members of the Working Group [pdf, 0.1 MB] B. Original terms of reference (Vladivostok, 1999) [pdf, 0.08 MB] C. Annual reports of WG 15 [pdf, 0.15 MB] D. Workshop report on taxonomy and identification of HAB species and data management [pdf, 0.15 MB] (Document pdf contains 156 pages)

Effects of temperature on the threshold of phosphorus for algal blooms

Algal blooms, worsening marine ecosystems and causing great economic loss, have been paid much attention to for a long time. Such environmental factors as light penetration, water temperature, and nutrient concentration are crucial in blooms processes. Among them, only nutrients can be controlled. Therefore, the threshold of nutrients for algal blooms is of great concern. To begin with, a dynamic eutrophication model has been constructed to simulate the algal growth and phosphorus cycling. The model encapsulates the essential biological processes of algal growth and decay, and phosphorus regeneration due to algal decay. The nutrient limitation is based upon commonly used Monod's kinetics. The effects of temperature and phosphorus limitation are particularly addressed. Then, we have endeavored to elucidate the threshold of phosphorus at different temperature for algal blooms. Based on the numerical simulation, the isoquant contours of change rate of alga as shown in the figure are obtained, which obviously demonstrate the threshold of nutrient at an arbitrary reasonable temperature. The larger the change rate is, the more rapidly the alga grows. If the phosphorus concentration at a given temperature remains larger than the threshold the algal biomass may increase monotonically, leading to the algal blooming. With the rising of temperature, the threshold is apparently reduced, which may explain why likely red tide disasters occur in a fine summer day. So, high temperature and sufficient phosphorus supply are the major factors which result in algal growth and blowout of red tide.

Ecophysiological perspectives of blue-green algal blooms

Blue-green algae (cyanobacteria) have had a profound and unparalled impact on the aquatic environment because of the phenomenon of bloom formation. In many countries, water management is threatened with extensive and persistent noxious blooms of blue-green algae in surface and near-surface mesotrophic and eutrophic waters. In view of this, ecological and physiological factors responsible for blue-green algal dominance are discussed. The implications of cyanobacterial blooms are highlighted and recommendations made to combat this menace

Discovery of viruses lysing blue-green algae in the Dneprovsk reservoirs. [Translation of: Water blooms (ed. A. V. Topachevskii) pp.171-174. Kiev, Naukova Dumka, 1968]

Viruses, which are characterised by a relative simplicity of chemical composition, are involved with all the groups of the animal and plant world. The discovery of viruses of lower organisms has special interest. Along with the already known viruses lysing bacteria and actinomycetes, viruses have been discovered in recent years which lyse algae. During investigations of water from water-bloom patches and of mud taken from zones of massive accumulation of blue-green algae in the Dneprovsk reservoirs, the authors obtained viruses lysing algae. The revealing of viruses producing lysis of blue-green algae, which one could use in the control of water-blooms, has the greatest interest. With this aim, samples of water were collected from various zones of water-bloom patches in the Kremenchug, Dneprovsk and Kukhov reservoirs. For viruses lysing algae we propose the name 'algophages'. Along with the existence of viruses of algae of the phage type, one cannot deny the possibility of the existence of viruses of another type, multiplying in the cells of algae and causing their virus illnesses.

Modelling algal blooms

This is the final report on the research project to develop predictive models to quantify algal blooms in relation to environmental variables. The project's objectives were to develop models simulating the impact of vertical structure and mass transfer upon the dynamics of planktonic algae, including cyanobacteria, in lakes and reservoirs, to assess the potential of sedimentary phosphorus to sustain algal growth following reduction in external loading and to expand and enhance formulations to predict behaviour of blue-green algal populations and to incorporate these into a model software package. As part of the project a strategy for the production of a user-friendly packaging for the modelling software PROTEC-2 adaptable to particular sites was developed.