Proactive Model Research Articles

PSPO: A Framework for Cost Effective Service Placement Optimization during enterprise modernization on Hybrid Clouds

An integrated cloud service model utilising both public and private cloud services to provide a holistic deployment of the enterprise applications is the need of the hour. Traditional existing applications getting modernised to meet the high business demands to serve end customers, by adapting technology enhancements towards big data and cloud to achieve the futuristic Service Level Agreements (SLA).Some efforts have been made to model with respect to cost and its impacts, yet the distinctive need is to get a holistic picture of the overall modernisation characteristics. In this paper, we propose a proactive cost optimisation model along with a proposed algorithm to solve some of the key issues towards service placement during enterprise modernisation. The proposed cost optimised algorithm is applied to different scenarios on multiple clouds with enterprise modernisation characteristics. Experimental results derived shown that the proposed work effectively optimises the service placement on multiple clouds.

PSPO: a framework for cost-effective service placement optimisation during enterprise modernisation on hybrid clouds

An integrated cloud service model utilising both public and private cloud services to provide a holistic deployment of the enterprise applications is the need of the hour. Traditional existing applications getting modernised to meet the high business demands to serve end customers, by adapting technology enhancements towards big data and cloud to achieve the futuristic Service Level Agreements (SLA).Some efforts have been made to model with respect to cost and its impacts, yet the distinctive need is to get a holistic picture of the overall modernisation characteristics. In this paper, we propose a proactive cost optimisation model along with a proposed algorithm to solve some of the key issues towards service placement during enterprise modernisation. The proposed cost optimised algorithm is applied to different scenarios on multiple clouds with enterprise modernisation characteristics. Experimental results derived shown that the proposed work effectively optimises the service placement on multiple clouds.

Miary podobieństw łańcuchów znakowych a deduplikacja rekordów w bibliograficznych bazach danych

Teza/cel artykułu – Celem artykułu jest przedstawienie metody deduplikacji/ łączenia (ang. deduplication/linkage) rekordów opisujących jednostki bibliograficzne w bazach danych opartej na miarach podobieństw łańcuchów znakowych. Algorytm opracowano na podstawie własnych doświadczeń nabytych podczas tworzenia bibliograficznej bazy danych oraz podczas realizacji badań bibliometrycznych, na podstawie publicznie dostępnych bibliograficznych baz danych. Formalny opis metody zilustrowano przykładami zaczerpniętymi z krajowej bibliograficznej bazy CYTBIN. Metody badawcze – Opracowanie metody wymagało przeglądu architektur informacyjnych wybranych krajowych bibliograficznych baz danych, określenia typologii problemów ich dotykających, wynikających nie tylko z przyjętych modeli składowania danych, ale i budowy graficznych interfejsów użytkownika, którymi są zasilane, analizy i wyboru miar podobieństw łańcuchów znakowych oraz ostatecznie zaproponowania miary złożonej umożliwiającej ewaluację podobieństwa rekordów bibliograficznych w oparciu o wartości ich atrybutów składowych. Wyniki – Przedstawione na przykładzie danych pochodzących z wybranej bazy bibliograficznej wyniki pozwoliły empirycznie zweryfikować użyteczność zaproponowanej metody. Dodatkowo dokonano analizy rozkładu podobieństwa rekordów bibliograficznych bazy CYTBIN określanego na podstawie zaproponowanej metody złożonej i metody opartej na mierze Jaro-Winkler wyliczanej dla tytułów jednostek bibliograficznych. Wnioski – Zaproponowana metoda, po dostrojeniu jej parametrów do specyfiki (występujących anomalii) konkretnych baz bibliograficznych, może być wprost zastosowana do poprawy jakości opisów bibliograficznych w nich gromadzonych, zarówno w proaktywnym modelu pracy (przed zatwierdzeniem opisu przez operatora), jak i modelu reaktywnym (weryfikacja wszystkich lub nowo zgromadzonych rekordów wykonywana np. w czasie mniejszego obciążenia systemu w dobowych odstępach czasu).

Proactive model based testing and evaluation for component-based systems

Embedded software systems are getting more and more complex. The demand for new features and functions led to an increasing complexity in the design and development of these systems. There are frequent reports in the media about software systems crashing and damages occurring due to software errors. One reason for this is that there are many software testing methods and techniques but they are often non-practical and difficult to use. The aim of the study was to improve existing testing methods and their practicality especially from the integrator viewpoint. Component-based system development, components of different granularities must be tested. Furthermore, an optimization approach based on simulated annealing is presented which is used to derive an integration order with respect to the proposed parameters in a powerful and reliable manner. The paper discusses explicit properties and the requirements that are to be verified, imposed upon software-intensive systems by their environment and by their users.

Proactive and reactive resource-constrained max-NPV project scheduling with random activity duration

This paper addresses the resource-constrained project problem in which activity durations are stochastic variables and the objective is to maximize the net present value of cash flow in the project. First, using the two classical time buffering methods, proactive scheduling optimization models are constructed to generate the robust schedules. Then, two reactive scheduling models with different objectives are proposed to adjust the baseline schedules when disruptions occur during their execution. For the NP-hardness of the studied problem, three heuristic algorithms, including tabu search (TS), variable neighbourhood search (VNS), and a mixed version of VNS and TS, are developed and compared with the multi-start iteration improvement algorithm through a computational experiment conducted on a randomly generated data set. In addition, based on the computational results obtained, the effects of several key parameters on the proactive and reactive scheduling results are analysed, and some managerial insights are obtained. The research in this paper has practical implications for contractors to improve the project profit in an uncertain environment.

‘Women and peace’

UN Security Council Resolution 1325 and the successive thematic resolutions together with a variety of reports have shaped the Women, Peace and Security (WPS) agenda. The ensuing policies and institutional responses try to deal with a variety of issues including women’s participation in peace-making initiatives and protection from sexual violence during armed conflict and in its aftermath. As such these responses are underpinned by a reactive approach with a focus on conflict and post-conflict gender-sensitive areas of intervention. While these remain worthwhile interventions, the WPS agenda, in spite of its name, inadequately addresses gender-sensitive areas in peace situations, regardless of the existence of conflicts. Building on feminist critiques of the WPS agenda and the findings and recommendations of the 2015 UN Global study on the implementation of Resolution 1325, the article argues that the WSP agenda and its prevention limb need to elaborate and integrate more explicitly and comprehensively a human rights strategy that shifts the focus from a reactive to a proactive model, one which pursues gender equality and women’s human rights in its own right, irrespective of whether conflicts erupt or not. A human rights infused WPS preventive agenda should be premised, on the one hand, on a clear understanding and endorsement of the meaning of gender equality, on the other hand, on the creation of mechanisms and process bolstering the role of international and regional human rights regimes. In particular, robust regional human rights systems have the potential to create fora for the participation of and interaction with domestic constituencies in the region. This in turn could lead to the elaboration of context sensitive, participatory solutions, grounded in international human rights law, to existing forms of discrimination against women, which during conflicts may be exacerbated, for example, in the form of sexual enslavement and abductions as reported in recent and less recent conflicts.

A proactive approach to solve integrated production scheduling and maintenance planning problem in flow shops

Abstract This paper deals with the integration of production scheduling and maintenance planning in order to optimize the bi-objective of quality robustness and solution robustness for flow shops with failure uncertainty. First, a proactive model is proposed to formulate the problem mathematically. Then, Monte Carlo sampling method is adopted to obtain the objective value for feasible solutions and a surrogate measure is proposed to approximate the objective function efficiently. Based on the sampling method and surrogate measure, a two-loop algorithm is devised to optimize the sequence of jobs, positions of preventive maintenances and idle times simultaneously. Computational results indicate that solution robustness and stability of quality robustness can be significantly improved using our algorithm compared with the solutions obtained by the traditional way.

Proactive and reactive models for disaster resilient supply chain

Natural or man-made disasters lead to disruptions across entire supply chain, hugely affecting the entire distribution system. Owing to disaster, the supply chain usually takes longer time to recover and eventually leads to loss in reputation and revenue. Therefore, business organizations are constantly focusing on making its distribution network of a supply chain resilient to either man-made or natural disasters in order to satisfy customer demand in time. The supply chain distribution network broadly comprises of two major decisions i.e. facility location and vehicle routing. The paper addresses these distribution decisions jointly as location-routing problem. The paper proposes Location-Routing Model with Time Windows using proactive and reactive approaches. In proactive approach, the risk factors are considered as preventive measure for disaster caused disruptions. The model is extended for reactive approach by considering the disruptions such as facility breakdowns, route blockages, and delivery delays with cost penalties. The case illustration is discussed for proactive approach. In case of disaster caused disruptions, the reactive approach is illustrated using three disruption case scenarios. Using both proactive and reactive approach, designing the distribution system can make the overall supply chain a disaster resilient supply chain.

Overcoming the Fear of the “Other”: Building Trust Between British Muslims and the Wider Community

Initiatives that seek to build community trust are timely given the increasing focus on terror-related attacks and the rise in associated hate crimes as well as scrutiny of the way Muslim leadership is responding to such incidents. This paper details a novel and proactive model that aims to improve and build trust between Muslims and the wider community. The Trust Building Project was found to accomplish its two objectives. Not only was there an improvement in participant knowledge of Islam scores but there was also evidence suggesting trust had improved through engagement, understanding and through getting to know one another. Listening and learning sought to dispel myths and highlight shared morals and values. We propose that through these interactions the basis to building a more trusting society can be formed. It is unclear to what extent this could reduce incidents of hate crime and discrimination, however social change has been shown to occur where there are grass roots initiatives and suggestions are made to examine how this work can be rolled out nationally in order to address the trust deficit seen within our society today.

Toward Socially Aware Robot Navigation in Dynamic and Crowded Environments: A Proactive Social Motion Model

Safe and social navigation is the key to deploying a mobile service robot in a human-centered environment. Widespread acceptability of mobile service robots in daily life is hindered by robot’s inability to navigate in crowded and dynamic human environments in a socially acceptable way that would guarantee human safety and comfort. In this paper, we propose an effective proactive social motion model (PSMM) that enables a mobile service robot to navigate safely and socially in crowded and dynamic environments. The proposed method considers not only human states (position, orientation, motion, field of view, and hand poses) relative to the robot but also social interactive information about human–object and human group interactions. This allows development of the PSMM that consists of elements of an extended social force model and a hybrid reciprocal velocity obstacle technique. The PSMM is then combined with a path planning technique to generate a motion planning system that drives a mobile robot in a socially acceptable manner and produces respectful and polite behaviors akin to human movements. Note to Practitioners —In this paper, we validated the effectiveness and feasibility of the proposed proactive social motion model (PSMM) through both simulation and real-world experiments under the newly proposed human comfortable safety indices. To do that, we first implemented the entire navigation system using the open-source robot operating system. We then installed it in a simulated robot model and conducted experiments in a simulated shopping mall-like environment to verify its effectiveness. We also installed the proposed algorithm on our mobile robot platform and conducted experiments in our office-like laboratory environment. Our results show that the developed socially aware navigation framework allows a mobile robot to navigate safely, socially, and proactively while guaranteeing human safety and comfort in crowded and dynamic environments. In this paper, we examined the proposed PSMM with a set of predefined parameters selected based on our empirical experiences about the robot mechanism and selected social environment. However, in fact a mobile robot might need to adapt to various contextual and cultural situations in different social environments. Thus, it should be equipped with an online adaptive interactive learning mechanism allowing the robot to learn to auto-adjust their parameters according to such embedded environments. Using machine learning techniques, e.g., inverse reinforcement learning [1] to optimize the parameter set for the PSMM could be a promising research direction to improve adaptability of mobile service robots in different social environments. In the future, we will evaluate the proposed framework based on a wider variety of scenarios, particularly those with different social interaction situations and dynamic environments. Furthermore, various kinds of social cues and signals introduced in [2] and [3] will be applied to extend the proposed framework in more complicated social situations and contexts. Last but not least, we will investigate different machine learning techniques and incorporate them in the PSMM in order to allow the robot to automatically adapt to diverse social environments.

Fostering Sustainable Development and Entrepreneurship: The New Role of University

Sustainable development is a global objective to overcome the economic, environment and society crises worldwide. The research aims are twofold: (i) Explores the proactive and dynamic model of the university’s education system, focusing on the new role played by the School of Economics in the promotion of economic, social and environmental sustainability, and how this goes beyond, in stimulating bottom–up social entrepreneurship ideas through students engagement; (ii) Provides a descriptive analysis of innovative laboratories modules, by studying and mapping the best project proposals initiated by the student. Finally, it presents a case study analysis on waste management (UniRecycling) project, scaling up objectives, stakeholder mapping, activities and the expected results. The findings show the new role played by School of Economics, along with other partner institutions, in supporting the student’s engagement in practice-oriented workshops that enable the transfer of knowledge, skills, and self – development. The implications of the research to be developed show that a dynamic bottom-up model of learning and dissemination of sustainable and entrepreneurial should aim to sensitise students to be active and create project ideas for social and environmental entrepreneurship and build and strengthen the local territorial networks, to contribute to the creation of a system of services attentive to responsible and sustainable entrepreneurial development.

能動的図書館サービスモデル，エンベディッド・ライブラリアンをめぐって：:アメリカにおける展開と日本における同様事項の追究（特集・第58回研究大会グループ研究発表）

能動的図書館サービスモデル，エンベディッド・ライブラリアンをめぐって：:アメリカにおける展開と日本における同様事項の追究（特集・第58回研究大会グループ研究発表）

Integrated Proactive Control Model for Energy Efficiency Processes in Facilities Management: Applying Dynamic Exponential Smoothing Optimization

Sustainable facilities management (SFM) opens the door of opportunity for companies to evaluate the quality of resources and environment management at their facilities. It enables the principles of sustainable development. There is still inefficiency in quantitative research of integrating environmental factors, particularly multi-source data, to monitor and control complicated systems in buildings. The objective of this research is to develop an effective method to dynamically optimize energy efficiency in SFM plans and strategies. The research question is: can the integrated proactive method reduce energy consumption with dynamically adjustable controls? This paper proposes a coordinated proactive control method using dynamic time-series prediction (PCM-DTSP) for SFM, which optimizes system controls by integrating the prediction results and monitored environmental-data. The results show that, after optimization, the temperature fluctuations are reduced to 33.3%. The average temperature and maximum temperature are reduced by 8% and 13.1%, respectively. The instantaneous power consumption was reduced by 0.17 KW per hour for each cooling system unit. The PCM-DTSP method can significantly optimize energy efficiency, which paves the way for long-term comprehensive energy management. The contribution of the research lies in its optimized control of energy consumption, temperature stabilization, and improvement of environmental comfort solutions, which can be generalized to various types of buildings.

The Age-Friendly Health System Imperative.

The unprecedented changes happening in the American healthcare system have many on high alert as they try to anticipate legislative actions. Significant efforts to move from volume to value, along with changing incentives and alternative payment models, will affect practice and the health system budget. In tandem, growth in the population aged 65 and older is celebratory and daunting. The John A. Hartford Foundation is partnering with the Institute for Healthcare Improvement to envision an age-friendly health system of the future. Our current prototyping for new ways of addressing the complex and interrelated needs of older adults provides great promise for a more-effective, patient-directed, safer healthcare system. Proactive models that address potential health needs, prevent avoidable harms, and improve care of people with complex needs are essential. The robust engagement of family caregivers, along with an appreciation for the value of excellent communication across care settings, is at the heart of our work. Five early-adopter health systems are testing the prototypes with continuous improvement efforts that will streamline and enhance our approach to geriatric care.

The Proactive Defense of Energy Internet Terminals Edge-Access Using the Network Topology Autoassociation

The “Stuxnet” event and the Ukraine blockout event caused by cyberattacks have shown that it is very important for power systems to implement proactive cyber defense. With the construction of energy internet, the terminal-edge accessing proactive defense technology of energy internet has drawn lots of attentions. This paper constructed the proactive defense model of energy internet terminals edge-access using the network topology autoassociation, and established the multi-path and multi-parameter stochastic communication path construction algorithm in energy internet terminals edge-access network. To solve the problem of the transmission reliability and defense revenue decline caused by the dynamic adjustment of the association cycle, we presented a novel algorithm based on non-extensive entropy and Renyi cross entropy, which measures the abnormal of real-time network with multi-feature. On this basis, the proactive adjustment strategy of network topology autoassociation communication paths and the dynamic threshold value judgment method were designed to improve the accuracy of network anomaly measuring. Moreover, this paper also proposed a cyber-security reliability prediction algorithm based on Hidden Markov prediction model, and presented the guide paths space proactive adjustment strategy and associated cycle stretching strategy based on the network topology autoasssociation diagram of reliability prediction, guaranteeing the service quality of terminal edge access network. Finally, the model was applied to carry out experimental analysis on DoS attack, following attack, semi-blind attack defense, and network communication service quality. Theoretical analysis and simulation results show that the applicability and accuracy of the proposed model and the adjustment strategy are valid, which can support the proactive defense of energy internet terminal edge-access.

Intergenerational Cooperation at the Workplace from the Management Perspective

AbstractThe labor market is currently experiencing employees of four generations. Each generation has different behavior patterns, attitudes, expectations, habits, and motivational mechanisms. As generational gaps play an important role in the business process, organizations have to find ways to balance the needs and views of different age groups. To overcome the negative outcomes arising from generational differences and to use the strengths of each generation, the implementation of comprehensive and proactive model of intergenerational cooperation, presented in the paper, is becoming the necessity for each organization because of the benefits.

A Proactive Model to Control Reactive Behaviors

Adaptation to change is not an easy process and sometimes does not happen at all. When people perceive that theirfreedom is going to be altered due to an unwanted change, they outwardly exhibit some symptomatic reactivebehaviors such as inertia, resistance, skepticism, and aggression. No matter how intense people’s reactance is, only afew of them may manage to examine the unwanted change more deeply and find a way to conform or adapt. Knowingthis, the current article focuses on a theoretical proactive model or a solution. The model mainly works on the idea ofrecognizing the symptomatic behavioral reactance of learners. In other words, in the face of the reactance-inducedbehaviors depicted in the model, the instructors can apply four proactive strategies of brainstorming, open transparentconversation, small scale project assignment and triple “c” rule by means of which they can walk learners safelytowards mutual trust, classroom stability and learner commitment. In the end, as the model is new, there is still enoughroom for further experimental researches on different aspects of the model in actual classroom settings.

A Proactive Service Model Facilitating Stream Data Fusion and Correlation

Stream data from devices and sensors is considered a typical kind of big data. Though being promising, they have a good prospect only when we can reasonably correlate and effectively use them. Herein, services come back to the spotlight. The paper reports some of the authors' efforts in promoting service-based fusion and correlation of such stream data in a real setting – monitoring and optimized coordination of individual devices in a power plant. This paper advocates a decentralized and service-based approach to dynamically correlating the sensor data and proactively generating higher-level events between sensors and applications. A novel service model for transforming and correlating massive stream data is proposed. This service model shows potential in realizing various middle-way programmable nodes to form larger-granularity and software-defined ‘sensors' in an IoT context.

Proactive modeling of water quality impacts of extreme precipitation events in a drinking water reservoir

Extreme precipitation events are of concern to managers of drinking water sources because these occurrences can affect both water supply quantity and quality. However, little is known about how these low probability events impact organic matter and nutrient loads to surface water sources and how these loads may impact raw water quality. This study describes a method for evaluating the sensitivity of a water body of interest from watershed input simulations under extreme precipitation events. An example application of the method is illustrated using the Wachusett Reservoir, an oligo-mesotrophic surface water reservoir in central Massachusetts and a major drinking water supply to metropolitan Boston. Extreme precipitation event simulations during the spring and summer resulted in total organic carbon, UV-254 (a surrogate measurement for reactive organic matter), and total algae concentrations at the drinking water intake that exceeded recorded maximums. Nutrient concentrations after storm events were less likely to exceed recorded historical maximums. For this particular reservoir, increasing inter-reservoir transfers of water with lower organic matter content after a large precipitation event has been shown in practice and in model simulations to decrease organic matter levels at the drinking water intake, therefore decreasing treatment associated oxidant demand, energy for UV disinfection, and the potential for formation of disinfection byproducts.

When doing nothing may be the best investment action: Pessimistic anticipative power transmission planning

Abstract A fundamental challenge in power system planning is how to handle the interactions of participants’ behaviors in deregulated markets. This is important due to the high cost involved in their decisions. Proactive or anticipative transmission expansion planning models have been proposed by some authors to jointly model the interactions among deregulated electricity market participants making market-driven investment decisions. Several works have shown that a Transmission Network Planner can increase social welfare by anticipating line expansion planning to generation expansion equilibrium and market outcomes. However, proactive transmission expansion decisions may lead to suboptimal solutions when the generation expansion equilibrium problem have multiple solutions (i.e., leading to higher total costs and lower social welfare). We propose a methodology to study the potential impacts of proactive expansion planning on generation expansion decisions. The resulting formulation is stated as a mathematical program subject to an equilibrium problem with equilibrium constraints (EPEC). To deal with this problem, we also propose an approach to derive tractable EPEC solutions with global optimality guaranteed based on a column-and-row generation algorithm. Our numerical results shows that a proactive investment plan can lead to higher total cost than not investing at all because of the existence of multiple market-driven generation expansion equilibria. We show that the proposed algorithm significantly reduce the time of computation up to two orders of magnitude with respect to existing methodologies.