bluuebunny/crossref_metadata_2025_split huggingface dataset:
A conceptual framework of impeders to strategy implementation from an exploratory case study in an Iranian university
Authors: Rahimnia Fariborz , Polychronakis Yiannis , Sharp John M. 
Published: November 2009

PurposeThe purpose of this paper is to develop a comprehensive framework for assessing impeders of strategy implementation in a higher education context through an in‐depth analysis of a higher education institution in Iran.Design/methodology/approachA semi‐structured interview is employed with senior academic staff and managers in a particular university.FindingsThe main impeders of strategy implementation within the university as the case organisation and are found to be grouped into five main areas: planning consequences, organisational, individual, managerial and environmental. The nature and reasons for the impeders are explained and finally an analytical framework is developed.Research limitations/implicationsThe paper, through the use of how and why questions during interviews, highlighted a framework which provides an in‐depth understanding of impeders. The paper's results have implications for other universities in Iran and indeed the Middle East. However, a limitation of this paper is that the results are exploratory only, given that the paper is carried out in only one Iranian university.Practical implicationsThis paper provides a valuable basis for discussion on the impeders of strategy implementation. Moreover, the results of the research can be used as guidance for managers and academic staff at the strategy implementation stage in the higher education sector.Originality/valueThe findings of the paper highlight the relevant impeders of strategy implementation within a higher education environment that will be of interest to those in this field, particularly those working in Iranian universities.
The impact of learning orientation on NSD and hotel performance
Authors: Tajeddini Kayhan 
Published: November 2009

PurposeAlthough the significance of the learning organization concept is recognised in innovation management, there are only a few studies on the way in which a learning orientation affects new service development (NSD) in the hotel industry in Iran. This paper aims to fill that gap.Design/methodology/approachA questionnaire is designed to ask hotel managers and owners for their thoughts on a range of organizational variables including the nature of learning orientation, NSD and the link with hotel business performance.FindingsUsing 129 hotels in Iran, it was found that NSD can be driven by higher levels of commitment to learning, shared vision and open‐mindedness. Furthermore, a regression analysis suggests that the effect of NSD on performance is positive.Research limitations/implicationsThis paper focuses on senior managers and owners of Iranian hotels who have a specific culture, history and experience. It would be useful to take a similar approach in other established industries with different cultural and environmental characteristics and experience, so that comparisons can be made.Practical implicationsThe findings reinforce the argument that a learning approach, coupled with organizational creativity, is the main prescription for a creative quality process. It also provides a quantum leap in an organization in terms of innovation. Evidence from this paper also shows the importance of managerial emphasis on creating an internal business environment conducive to innovative activities.Originality/valueThe paper shows how learning deficiency is one of the main reasons that companies find it difficult to remain successful in the market.
Identification of knowledge management critical success factors in Iranian academic research centers
Authors: Akhavan Peyman , Hosnavi Reza , Sanjaghi Mohammad E. 
Published: November 2009

PurposeThe purpose of this paper is to examine the status of knowledge management (KM) in selected Iranian academic research centers (IARCs) in order to identify the most relevant KM critical success factors adopted by those centers that include physics, chemical, drug, aerospace, nanotechnology, mechanic, aviation, and biotechnology research centers.Design/methodology/approachBased on extensive review of KM literature, broad ranges of general KM critical success factors are identified. Then, through field studies, the degree of the relevance of each particular KM success factor is determined. The research procedure finally led to the identification of KM critical success factors prevailing in IARCs.FindingsFive distinct KM factors including 16 different elements are found to be relevant and critical in the course of KM implementation in IARCs. These factors are “human resource management and flexible structures,” “KM architecture and readiness,” “knowledge storage,” “benchmarking,” and “chief knowledge officer.”Research limitations/implicationsThe extracted factors can act as a guideline for KM preliminary phases in organizations. This helps to ensure that the essential issues are covered during the design and implementation phase of a KM program. For academics, it may provide a common language for discussion and study of the factors crucial for KM.Originality/valueThe paper should be of value to researchers of KM in general, and to implementers of KM programs. It presents a range of issues critical to the adoption of KM initiatives.
Deductive verification of simple foraging robotic behaviours
Authors: Behdenna Abdelkader , Dixon Clare , Fisher Michael 
Published: November 2009

PurposeThe purpose of this paper is to consider the logical specification, and automated verification, of high‐level robotic behaviours.Design/methodology/approachThe paper uses temporal logic as a formal language for providing abstractions of foraging robot behaviour, and successively extends this to multiple robots, items of food for the robots to collect, and constraints on the real‐time behaviour of robots. For each of these scenarios, proofs of relevant properties are carried out in a fully automated way. In addition to automated deductive proofs in propositional temporal logic, the possibility of having arbitrary numbers of robots involved is considered, thus allowing representations of robot swarms. This leads towards the use of first‐order temporal logics (FOTLs).FindingsThe proofs of many properties are achieved using automatic deductive temporal provers for the propositional and FOTLs.Research limitations/implicationsMany details of the problem, such as location of the robots, avoidance, etc. are abstracted away.Practical implicationsLarge robot swarms are beyond the current capability of propositional temporal provers. Whilst representing and proving properties of arbitrarily large swarms using FOTLs is feasible, the representation of infinite numbers of pieces of food is outside of the decidable fragment of FOTL targeted, and practically, the provers struggle with even small numbers of pieces of food.Originality/valueThe work described in this paper is novel in that it applies automatic temporal theorem provers to proving properties of robotic behaviour.
Distributed adaptive swarm for obstacle avoidance
Authors: Hettiarachchi Suranga , Spears William M. 
Published: November 2009

PurposeThe purpose of this paper is to demonstrate a novel use of a generalized Lennard‐Jones (LJ) force law inPhysicomimetics, combined with offline evolutionary learning, for the control of swarms of robots moving through obstacle fields towards a goal. The paper then extends the paradigm to demonstrate the utility of a real‐time online adaptive approach named distributed agent evolution with dynamic adaptation to local unexpected scenarios (DAEDALUS).Design/methodology/approachTo achieve the best performance, the parameters of the force law used in the Physicomimetics approach are optimized, using an evolutionary algorithm (EA) (offline learning). A weighted fitness function is utilized consisting of three components: a penalty for collisions, lack of swarm cohesion, and robots not reaching the goal. Each robot of the swarm is then given a slightly mutated copy of the optimized force law rule set found with offline learning and the robots are introduced to a more difficult environment. The online learning framework (DAEDALUS) is used for swarm adaptation in this more difficult environment.FindingsThe novel use of the generalized LJ force law combined with an EA surpasses the prior state‐of‐the‐art in the control of swarms of robots moving through obstacle fields. In addition, the DAEDALUS framework allows the swarms of robots to not only learn and share behavioral rules in changing environments (in real time), but also to learn the proper amount of behavioral exploration that is appropriate.Research limitations/implicationsThere are significant issues that arise with respect to “wall following methods” and “local minimum trap” problems. “Local minimum trap” problems have been observed in this paper, but this issue is not addressed in detail. The intention is to explore other approaches to develop more robust adaptive algorithms for online learning. It is believed that the learning of the proper amount of behavioral exploration can be accelerated.Practical implicationsIn order to provide meaningful comparisons, this paper provides a more complete set of metrics than prior papers in this area. The paper examines the number of collisions between robots and obstacles, the distribution in time of the number of robots that reach the goal, and the connectivity of the formation as it moves.Originality/valueThis paper addresses the difficult task of moving a large number of robots in formation through a large number of obstacles. The important real‐world constraint of “obstructed perception” is modeled. The obstacle density is approximately three times the norm in the literature. The paper shows how concepts from population genetics can be used with swarms of agents to provide fast online adaptive learning in these challenging environments. In addition, this paper also presents a more complete set of metrics of performance.
Model independence in swarm robotics
Authors: Kazadi S. 
Published: November 2009

PurposeThe purpose of this paper is to examine and illustrate the development of a methodology for generating swarms using lossless flocking.Design/methodology/approachA general methodology for swarm design is described. Examples of this approach in the literature are examined. A general requirement for lossless flocking is developed. The requirement is used in developing two swarm behaviors.FindingsIt is possible to apply the approach to the lossless flocking and to use the swarm condition to develop two swarm behaviors which satisfy this condition in many situations.Research limitations/implicationsThis paper illustrates the general swarm engineering method and demonstrates how it can be properly applied.Originality/valueThe swarm engineering method is used to develop the “quark” model, a new physicomimetic model.
Decentralized evolution of robotic behavior using finite state machines
Authors: König Lukas , Mostaghim Sanaz , Schmeck Hartmut 
Published: November 2009

PurposeIn evolutionary robotics (ER), robotic control systems are subject to a developmental process inspired by natural evolution. The purpose of this paper is to utilize a control system representation based on finite state machines (FSMs) to build a decentralized online‐evolutionary framework for swarms of mobile robots.Design/methodology/approachA new recombination operator for multi‐parental generation of offspring is presented and a known mutation operator is extended to harden parts of genotypes involved in good behavior, thus narrowing down the dimensions of the search space. A storage called memory genome for archiving the best genomes of every robot introduces a decentralized elitist strategy. These operators are studied in a factorial set of experiments by evolving two different benchmark behaviors such as collision avoidance and gate passing on a simulated swarm of robots. A comparison with a related approach is provided.FindingsThe framework is capable of robustly evolving the benchmark behaviors. The memory genome and the number of parents for reproduction highly influence the quality of the results; the recombination operator leads to an improvement in certain parameter combinations only.Research limitations/implicationsFuture studies should focus on further improving mutation and recombination. Generality statements should be made by studying more behaviors and there is a need for experimental studies with real robots.Practical implicationsThe design of decentralized ER frameworks is improved.Originality/valueThe framework is robust and has the advantage that the resulting controllers are easier to analyze than in approaches based on artificial neural networks. The findings suggest improvements in the general design of decentralized ER frameworks.
Adaptive swarm behavior acquisition by a neuro‐fuzzy system and reinforcement learning algorithm
Authors: Kuremoto Takashi , Obayashi Masanao , Kobayashi Kunikazu 
Published: November 2009

PurposeThe purpose of this paper is to present a neuro‐fuzzy system with a reinforcement learning algorithm (RL) for adaptive swarm behaviors acquisition. The basic idea is that each individual (agent) has the same internal model and the same learning procedure, and the adaptive behaviors are acquired only by the reward or punishment from the environment. The formation of the swarm is also designed by RL, e.g. temporal difference (TD)‐error learning algorithm, and it may bring out a faster exploration procedure comparing with the case of individual learning.Design/methodology/approachThe internal model of each individual composes a part of input states classification by a fuzzy net, and a part of optimal behavior learning network which adopting a kind of RL methodology named actor‐critic method. The membership functions and fuzzy rules in the fuzzy net are adaptively formed online by the change of environment states observed in the trials of agent's behaviors. The weights of connections between the fuzzy net and the action‐value functions of actor which provides a stochastic policy of action selection, and critic which provides an evaluation to state transmission, are modified by TD‐error.FindingsSimulation experiments of the proposed system with several goal‐directed navigation problems are accomplished and the results show that swarms are successfully formed and optimized routes are found by swarm learning faster than the case of individual learning.Originality/valueTwo techniques, i.e. fuzzy identification system and RL algorithm, are fused into an internal model of the individuals for swarm formation and adaptive behavior acquisition. The proposed model may be applied to multi‐agent systems, swarm robotics, metaheuristic optimization, and so on.
A review and implementation of swarm pattern formation and transformation models
Authors: Varghese Blesson , McKee Gerard 
Published: November 2009

PurposeThe purpose of this paper is to address a classic problem – pattern formation identified by researchers in the area of swarm robotic systems – and is also motivated by the need for mathematical foundations in swarm systems.Design/methodology/approachThe work is separated out as inspirations, applications, definitions, challenges and classifications of pattern formation in swarm systems based on recent literature. Further, the work proposes a mathematical model for swarm pattern formation and transformation.FindingsA swarm pattern formation model based on mathematical foundations and macroscopic primitives is proposed. A formal definition for swarm pattern transformation and four special cases of transformation are introduced. Two general methods for transforming patterns are investigated and a comparison of the two methods is presented. The validity of the proposed models, and the feasibility of the methods investigated are confirmed on the Traer Physics and Processing environment.Originality/valueThis paper helps in understanding the limitations of existing research in pattern formation and the lack of mathematical foundations for swarm systems. The mathematical model and transformation methods introduce two key concepts, namely macroscopic primitives and a mathematical model. The exercise of implementing the proposed models on physics simulator is novel.
A swarm of robots using RFID tags for synchronization and cooperation
Authors: Zecca Giulio , Couderc Paul , Banâtre Michel , Beraldi Roberto 
Published: November 2009

PurposeThe purpose of this paper is to show how a swarm of robots can cooperate to achieve a common task, in a totally distributed and autonomous way, by exploiting powerful clues contained in some devices that are distributed in the environment. This system exploits a coordination mechanism that is twofold, using radio frequency identification (RFID) tags for spatial coordination, and wireless robot‐to‐robot communication for the temporal and semantic synchronization.Design/methodology/approachProgress in the pervasive computing field has led to the distribution of knowledge and computational power in the environment, rather than condensing it in a single, powerful entity. This vision of ambient intelligence is supported by the interchange of information between physically sparse agents cooperating to achieve a common goal. An emerging method for this kind of collaboration considers the agents as insects in a swarm, having the possibility of communicating directly or indirectly with each other. The goal is to fulfill a common task, showing that a collaborative behavior can be useful in the real world. The paper focuses on a technique for the coordination of swarm‐robots with low capabilities, driven by instructions learned from RFID tags used as distributed pervasive memories. These robots exploit ubiquitous computing to regroup in a synchronization area, make a formation in space, coordinate with team‐mates in the same zone, and finally complete a cooperative task. The algorithm is validated through a simulation environment, showing its applicability and performance, before the real implementation on Roomba‐like robots.FindingsThe goal of the research is to prove the feasibility of such a novel approach. It is observed that a swarm of robots can achieve a good degree of autonomous cooperation without a central infrastructure or global network, carrying out a goal in a fair time.Originality/valueThe value is given by the benefits of splitting the synchronization semantics into two levels: space, by exploiting RFID landmarks; and time, by exploiting wireless short‐range communication. RFID tags are used to distribute computational power and actively interact with the surrounding areas, allowing to learn and modify the state of the environment. Robot‐to‐robot communication, instead, is used for providing timing and semantic information. In the proposal, this augmented environment is used to allow a good level of coordination among robots, both in time and space, with the aim of building a cooperative system.
Inhibition of MMP‐9 transcription and suppression of tumor metastasis by pyrrole‐imidazole polyamide
Authors: Wang Xiaofei , Nagase Hiroki , Watanabe Takayoshi , Nobusue Hiroyuki , Suzuki Tsukasa , Asami Yukihiro , Shinojima Yui , Kawashima Hiroyuki , Takagi Keiko , Mishra Rajeev , Igarashi Jun , Kimura Makoto , Takayama Tadatoshi , Fukuda Noboru , Sugiyama Hiroshi 
Published: November 2009

(Cancer Sci 2010; 101: 759–766)Matrix metalloproteinase (MMP)‐9, the 92‐kDa type IV collagenase, contributes to tumor invasion and metastases, and strategies to down‐regulate its expression could ultimately be of clinical utility. A pyrrole‐imidazole (PI) polyamide that targets the activator protein‐1 (AP‐1)‐binding site of the MMP‐9 promoter was designed and synthesized as a gene‐silencing agent for tumor metastases. The synthesized product showed selective DNA binding ability. The MMP‐9 PI polyamide significantly inhibited MMP‐9’s mRNA expression, protein level, and enzymatic activity in human breast adenocarcinoma cells (MDA‐MB‐231). Furthermore, the MMP‐9 PI polyamide inhibited migration and invasion by in vitro wound‐healing and matrigel‐invasion assay. The FITC‐labeled PI polyamide was localized in nuclei in 45 min of incubation with an MDA‐MB‐231 cell and remained in the nuclei for up to 96 h after incubation in vitro. It was also quickly localized in the mouse cellular nuclei of many tissues, including liver, kidney, and spleen, after intravenous injection without using any drug‐delivery system. Moreover, the polyamide treatment significantly decreased metastasis in a mouse model of liver metastasis. Our results suggest that this PI polyamide, which targets the MMP‐9 gene promoter, can be a novel MMP‐9 down‐regulating molecule for antimetastasis.
Role of tumor‐associated lymphatic endothelial cells in metastasis: A study of epithelial ovarian tumor in vitro
Authors: Yang Shouhua , Zhu Xiaowu , Cai Liqiong , Cheng Henghui , Zhao Rongwei , Wang Hongbo , Zhao Hong , Wang Zehua 
Published: November 2009

(Cancer Sci 2010; 101: 679–685)Tumor‐associated lymphatic endothelial cells (TLEC) could play a key role in the process of tumor metastasis. The aim of this study was to investigate the effect of TLECs that were isolated from human epithelial ovarian tumor (EOT) on ovarian cancer cell line CAOV‐3 in vitro. First, TLECs in EOT were detected by immunochemistry and flow cytometry, then marked by lymphatic endothelial cell (LEC) marker LYVE‐1, isolated by magnetic beads, and cultured in vitro. The cells were identified by immunostaining of LEC markers LYVE‐1, Prox‐1, Podoplanin, VEGFR‐3, and pan‐endothelial cell marker CD31. TLECs from EOT can be detected, cultured, and identified in vitro successfully. The effects of TLECs on invasion and migration of CAOV‐3 cells were investigated by 12‐well Boyden chamber; the proliferation effect was studied by counting the Trypan blue exclusion cell number. Furthermore, changes in MMP‐2/9 secreted by CAOV‐3 cells treated with TLEC were shown using real‐time PCR and zymography, and TIMP‐1/2 was detected by real‐time PCR. In vitro, TLECs can enhance invasion and migration of CAOV‐3 cells, but have no significant effect on proliferation. It was clear that the expression of MMP‐9 increased and TIMP‐2 decreased in CAOV‐3 cells treated by TLECs, and the increasing of MMP‐9 was confirmed by zymography. TLECs from EOT can enhance migration and invasion of human ovarian carcinoma cell line in vitro, and the possible mechanism was through activation of MMP‐9/TIMP‐2.
Rubratoxin A specifically and potently inhibits protein phosphatase 2A and suppresses cancer metastasis
Authors: Wada Shun‐ichi , Usami Ihomi , Umezawa Yoji , Inoue Hiroyuki , Ohba Shun‐ichi , Someno Tetsuya , Kawada Manabu , Ikeda Daishiro 
Published: November 2009

(Cancer Sci 2010; 101: 743–750)Although cytostatin analog protein phosphatase 2A (PP2A)‐specific inhibitors are promising candidates of a new type of anticancer drug, their development has been hindered because of their liability. To find new classes of PP2A‐specific inhibitors, we conducted a screening with microbial metabolites and found that rubratoxin A, a classical mycotoxin, is a highly specific and potent inhibitor of the enzyme. While rubratoxin A inhibits PP2A at Ki = 28.7 nm, it hardly inhibited any other phosphatases examined. Rubratoxin B, a close analog, also specifically but weakly inhibits PP2A at Ki = 3.1 μm. The inhibition of intracellular PP2A in cultured cells is obviously observed with 20 μm rubratoxin A treatment for 3 h, inducing the overphosphorylation in PP2A substrate proteins. Although rubratoxins and cytostatin differ in the apparent structures, these compounds share similarities in the structures in detail and PP2A‐binding manners. Rubratoxin A showed higher suppression of tumor metastasis and reduction of the primary tumor volume than cytostatin in mouse experiments. As a successor of cytostatin analogs, rubratoxin A should be a good compound leading to the development of antitumor drugs targeting PP2A.