Three-phase Strategy Research Articles

Uncertainty Management in Context-Aware Applications: Increasing Usability and User Trust

Uncertainty in context-aware computing is mainly a consequence of the complexity of context acquisition mechanisms and context processing. The presence of uncertainty may harm the users' confidence in the application, rendering it useless. This paper describes a three-phase strategy to manage uncertainty by identifying its possible sources, representing uncertain information, and determining how to proceed, once uncertain context is detected. We conducted an experiment to assess the impact and utility of uncertainty management in a location-aware museum guide that incorporated the approach proposed. The impact was measured by comparing the number of erroneous location estimations and the number of interactions performed by users. A survey was used to measure user friendliness, the utility of the application and user trust among 118 museum visitors who participated in the experiment. Results suggest that uncertainty management helps improve the accuracy of context estimates and the user's perception on the reliability of the application.

Designing a knowledge transfer and exchange strategy for the Alberta Depression Initiative: contributions of qualitative research with key stakeholders

BackgroundDepressive disorders are highly prevalent and of significant societal burden. In fall 2004, the 'Alberta Depression Initiative' (ADI) research program was formed with a mission to enhance the mental health of the Alberta population. A key expectation of the ADI is that research findings will be effectively translated to appropriate research users. To help ensure this, one of the initiatives funded through the ADI focused specifically on knowledge transfer and exchange (KTE). The objectives of this project were first to examine the state of the KTE literature, and then based on this review and a set of key informant interviews, design a KTE strategy for the ADI.MethodsFace to face interviews were conducted with 15 key informants familiar with KTE and/or mental health policy and programs in Alberta. Interviews were transcribed and analyzed using the constant comparison method.ResultsThis paper reports on findings from the qualitative interviews. Respondents were familiar with the barriers to and facilitators of KTE as identified in the existing literature. Four key themes related to the nature of effective KTE were identified in the data analysis: personal relationships, cultivating champions, supporting communities of practice, and building receptor capacity. These recommendations informed the design of a contextually appropriate KTE strategy for the ADI. The three-phased strategy involves preliminary research, public workshops, on-going networking and linkage activities and rigorous evaluation against pre-defined and mutually agreed outcome measures.ConclusionInterest in KTE on the part of ADI has led to the development of a strategy for engaging decision makers, researchers, and other mental health stakeholders in an on-going network related to depression programs and policy. A similarly engaged process might benefit other policy areas.

Uncertainty Modeling of Improved Fuzzy Functions With Evolutionary Systems

This paper introduce a type-2 fuzzy function system for uncertainty modeling using evolutionary algorithms (ET2FF). The type-1 fuzzy inference systems (FISs) with fuzzy functions, which do not entail if ... then rule bases, have demonstrated better performance compared to traditional FIS. Nonetheless, the performance of these approaches is usually affected by their uncertain parameters. The proposed method implements a three-phase learning strategy to capture the uncertainties in fuzzy function systems induced by learning parameters, as well as fuzzy function structures. The improved fuzzy clustering initially finds hidden structures, and the genetic learning algorithm optimizes interval type-2 fuzzy sets to capture their optimum uncertainty interval. The proposed ET2FF architecture is evaluated using an extensive suite of real-life applications such as manufacturing process and financial market modeling. The results show that the proposed ET2FF method is comparable--if not superior--to earlier FIS in terms of generalization performance and robustness.

Regenerative Strategy for Fairness in Bi-directional Three-Node Relaying

The fairness solution without deteriorating the system sum-rate is a challenge under a total energy constraint. One regenerative strategy is proposed to improve the fairness for bi-directional three-node relaying, which is based on decode-and-forward technique with network coding and power optimization. In this letter, the application of network coding decreases the number of transmission phases from traditional four phases to three phases. Moreover, the proposed power optimization algorithm can be applied in practical system, which transforms max-min optimization problem to linear programming (LP) with low complexity. Numerical simulations shows this strategy enhances the minimum of unidirectional transmission rate up to 94% as compared to a four-phase bi-directional strategy, and up to 46% as compared to the three-phase bi-directional strategy with equal-power allocation.

Three-phase strategy for the OSD learning method in RBF neural networks

This paper presents a novel approach in learning algorithms commonly used for training radial basis function (RBF) neural networks. This approach could be used in applications that need real-time capabilities for retraining RBF neural networks. The proposed method is a Three-Phase Learning Algorithm that optimizes the functionality of the Optimum Steepest Decent (OSD) learning method. This methodology focuses to attain greater precision in initializing the center and width of RBF units. An RBF neural network with well-adjusted RBF units in the train process will result in better performance in network response. This method is proposed to reach better performance for RBF neural networks in fewer train iterations, which is the critical issue in real-time applications. Comparing results employing different learning strategies shows interesting outcomes as have come out in this paper.

Hybrid Scheduling of Dynamic Task Graphs with Selective Duplication for Multiprocessors under Memory and Time Constraints

This paper presents a hybrid scheduling methodology for task graphs to multiprocessor embedded systems. The proposed methodology is designed for task graphs that are dynamic in nature due to the presence of conditional tasks and tasks whose execution times are unpredictable but bounded. We have presented the methodology as a three-phase strategy, in which task nodes are mapped to the processors in the first (static mapping) phase. In the second (selective duplication) phase, some critical nodes are identified and duplicated for possible rescheduling at runtime, depending on the code memory constraints of the processors. The third (online) phase is a runtime scheduling algorithm that performs list scheduling based on the actual dynamics of the schedule up to the current time. We show that this technique provides better schedule length (up to 20 percent) compared to previous techniques, which are predominantly static in nature, with low overhead and a complexity comparable with existing online techniques. The effects of model parameters like the number of processors, memory, and various task graph parameters on performance are investigated in this paper.

Detecting Arbitrary Stable Properties Using Efficient Snapshots

A stable properly continues to hold in an execution once it becomes true. Detecting arbitrary stable properties efficiently in distributed executions is still an open problem. The known algorithms for detecting arbitrary stable properties and snapshot algorithms used to detect such stable properties suffer from drawbacks such as the following: They incur the overhead of a large number of messages per global snapshot, or alter application message headers, or use inhibition, or use the execution history, or assume a strong property such as causal delivery of messages in the system. We solve the problem of detecting an arbitrary stable property efficiently under the following assumptions: P1) the application messages should not be modified, not even by timestamps or message coloring. P2) no inhibition is allowed. P3) the algorithm should not use the message history. P4) any process can initiate the algorithm. This paper proposes a family of nonintrusive algorithms requiring 6(n - 1) control messages, where n is the number of processes. A three-phase strategy of uncoordinated observation of local states is used to give a consistent snapshot from which any stable property can be detected. A key feature of our algorithms is that they do not rely on the processes continually and pessimistically reporting their activity. Only the relevant activity that occurs in the thin slice during the algorithm execution needs to be examined.

People and their waste in an emergency context: The case of Monrovia, Liberia

Liberia has gone through civil crisis for over a decade which has resulted in the destruction of infrastructure and disruption of basic services delivery particularly in Monrovia, the capital city. Most of the 1.3 million people living in Monrovia are without adequate environmental sanitation and waste management services which situation poses a serious health risk to the residents. The current waste management service coverage is less than 20% and disposal is by indiscriminate open dumping. In 2003, there were series of outbreaks of cholera epidemics in the city during which time a total of 26,651 cases were reported with many dying. The waste management plan was initiated as an exit strategy of UNICEF following an intervention response programme to assist the Monrovia City Corporation (MCC) whose capacity in this area had been crippled as a result of years of war, through the provision of support in solid waste collection and disposal. The objectives of the plan were to: (a) Improve waste management services delivery in the city. (b) Strengthen the ability of the MCC to plan and manage the waste services delivery. (c) Enhance cooperation of service beneficiaries through comprehensive and effective health education and service promotional campaign. (d) Enhance revenue generation and community participation through the promotion of private sector and CBOs/NGOs active involvement in the waste management service delivery. The general methodology adopted for the assignment entailed the following: Desk study and review of existing reports on Water and Environmental Sanitation (WES) in Monrovia and other relevant literature, consultation with stakeholders, site visits and participatory planning which aimed at soliciting the opinions of the various stakeholders involved with the respective components to capture their aspirations and experiences. It also covered collection and analysis of available information and data to facilitate the plan preparation and facilities design. The three-phased strategy (short, medium and long term) covering a period of 10 years (August 2004–December 2014), recommended a combination of technical options for collection based on the pursuit of staged development to allow for the adoption of realistically attainable standards within a framework of continuous and systematic improvements as economic conditions improved and new knowledge gained through practice. The plan sought to blend the capacity within the City Corporation with that of the private sector and NGOs/CBOs to respond to the diverse service demands of the city taking into consideration housing and infrastructural conditions, service costs and cost recovery to ensure sustainability. It also identified sources of financing and allocated financing responsibilities to facilitate effective plan implementation.

A three-phase sampling strategy for large-scale multiresource forest inventories

This article considers a two-phase estimation for the areal extent of K land categories partitioning a study region and a three-phase estimation for the biomass of W forest categories out of the K. In the first phase, a sample of N points is selected according to the unaligned systematic sampling. In the second phase, the selected points are partitioned into L strata on the basis of aerial photos. Then, a total sample of n < N points is selected by stratified sampling and the selected points are visited on the ground and correctly classified into one of K categories. The information achieved in the second phase is sufficient for obtaining an unbiased estimator of the areal extent vector together with a conservative estimator of its variance-covariance matrix. As to the estimation of the biomass of the W forest categories, in the third phase the second-phase sample is further partitioned into substrata on the basis of ground information. Finally, a total sample of m < n points is selected by stratified sampling. Then a plot of adequate radius centered at each point is considered and the biomass is recorded within. An unbiased estimator of the biomass vector is derived together with a conservative estimator of its variance-covariance matrix. The proposed strategy also makes it possible to obtain the calibrated estimator of the areal extent vector as well as estimators for the sums or ratios of the areal extents and biomasses. The application of the strategy in the Italian National Forest Inventory is considered.

STRATEGY OF SOLUTION FOR THE INVENTORY ROUTING PROBLEM BASED ON SEPARABLE CROSS DECOMPOSITION

The Inventory-Routing Problem (IRP) involves a central warehouse, a fleet of trucks wlth finlte capacity, a set of customers, and a known storage capacity. The objective is to determine when to serve each customer, as well as what route each truck should take, with the lowest expense. IRP is a NP-hard problem, this means that searching for solutions can take a very long time. A three-phase strategy is used to solve the problem. This strategy is constructedn by answering the key questions: Which customers should be attended in a planned period? What volume of n products should be delivered to each customer? And, which route should be followed by each truck? The second phase uses Cross Separable Decomposition to solve an Allocation Problem, in order to answer questions two and three, solving a location problem. The result is a very efficient ranking algorithm O(n3) for large cases of the lRP.

Proteomic Analysis of Cleavage Events Reveals a Dynamic Two-step Mechanism for Proteolysis of a Key Parasite Adhesive Complex

The transmembrane micronemal protein MIC2 and its partner M2AP comprise an adhesive complex that is required for rapid invasion of host cells by the obligate intracellular parasite Toxoplasma gondii. Recent studies have shown that the MIC2/M2AP complex undergoes extensive proteolytic processing on the parasite surface during invasion, including primary processing of M2AP by unknown proteases and proteolytic shedding of the complex by an anonymous protease called MPP1. While it was shown that MPP1-mediated cleavage is necessary for efficient invasion, it remained unclear whether the adhesive complex was liberated by juxtamembrane or intramembrane proteolysis. Here, using a three-phase strategy of assigning cleavage sites based on intact matrix-assisted laser desorption/ionization mass followed by confirmation by enzymatic digestion and inhibitor profiling, we demonstrate that M2AP is processed by two parasite-derived proteases called MPP2 and MPP3. We also define the substrate repertoire of MPP2 by two-dimensional differential gel electrophoresis using fluorescent tags. Finally, we use complementary mass spectrometric techniques to unequivocally show that MIC2 is shed by intramembrane cleavage within its anchoring domain. Based on the properties of this cleavage site, we conclude that the sheddase, MPP1, is likely a multipass membrane protease of the Rhomboid family. Our data support a novel two-step proteolysis model that includes primary processing of the MIC2/M2AP complex followed by secondary cleavage to shed the complex from the parasite surface during the final steps of invasion.

QT interval prolongation by noncardiovascular drugs: A proposed assessment strategy

The aim of the present article is to propose a pragmatic approach to the assessment of cardiac risk for noncardiovascular medicinal products. The clinical and pharmacological background to drug-induced cardiac arrhythmia is reviewed, in particular concerning the relationship between prolonged QT intervals in the ECG and often fatal torsades de pointes (TDP) in humans. In vitro and in vivo approaches are compared, and it is concluded that in vivo techniques are more appropriate for risk assessment, whereas in vitro techniques, including analysis of Purkinje fibers, are primarily useful for elucidating mechanisms. The study of monophasic action potentials (MAPs) is suggested to represent a useful bridge between in vitro and in vivo. A three-phase risk assessment strategy is proposed. The first phase uses telemetry in freely moving conscious dogs. If signs of QT prolongation or changes in T or U wave morphology are detected, this should be confirmed in a second phase by studying MAPs in anesthetized dogs under paced and nonpaced conditions (to rule out artifacts). Only if the presence of risk is confirmed should in vitro techniques, for example, analysis of Purkinje fibers, be employed for explanatory purposes. Drug Dev. Res. 47:55–62, 1999. © 1999 Wiley-Liss, Inc.

Attitudes of Low-income Indivi duals Towards Entrepreneurship: An Assessment

This paper develops a framework to assess the attitudes of low-income individu als toward entrepreneurship on the basis of a survey of the residents of a public housing in a major south-western city in the United States. These attitudes are treated by the study as consequences of the conditions and context of life of the urban poor. Recognising the significance of entrepreneurship as a solution to urban poverty, it proposes a three-phase strategy to attract and motivate low- income individuals to take up entrepreneurial ventures.

Vegetative Architecture ofElaeocarpus hookerianus.Transition from Juvenile to Adult

Elaeocarpus hookerianus Raoul is a profoundly heteroblastic tree native to New Zealand. We describe and quantify changes in leaf morphology and anatomy, and in branching pattern at dierent levels of insertion. Discrete juvenile, adolescent and adult phases were identified. The divaricating juvenile bore small leaves with thin laminae and an anatomy typical of shade-plants. Juveniles had dense canopies, many thin horizontal and vertical axes, wide branch angles and highly variable branching patterns. Adolescents had larger leaves, fewer horizontal axes on a single, leading vertical axis, and a more consistent branching pattern. Adults were arborescent, producing the largest, most dierentiated leaves on the stoutest and longest horizontal branches. Data indicate a three-phased strategy for: (a) providing responsive, energy-ecient shoot systems under low-light regimes; (b) growing rapidly to the forest canopy; and (c) exploiting for the forest canopy environment. # 1997 Annals of Botany Company

Dealing with the Dilemmas Posed by Power Asymmetry in Intergroup Conflict

Some methods of unofficial intervention in protracted intercommunal conflict fail to consider the impact of power asymmetry on the dynamics of conflict and the predictably divergent goals that lower- and higher-power groups seek in unofficial meetings. As a result, third parties face the dilemma of trying to satisfy seemingly irreconcilable goals of the conflicting parties. This article examines asymmetry of goals and the further dilemmas it creates in choosing the level of discourse in unofficial meetings, and in recruiting participants. The authors propose a more proactive research focus on the dynamics of power asymmetry and advance a three-phase strategy for practitioners to deal with the dilemmas of intervening in asymmetrical conflict.

Supervisory Control of Drilling

A supervisory process control approach to machining is presented in this paper, and demonstrated by application to a drilling operation. The supervisory process control concept incorporates optimization and control functions in a hierarchical structure. This approach utilizes feedback measurements to parameterize the constraints of a process optimization problem whose solution determines both strategies and references for process control. For this particular drilling operation, a three-phase strategy (utilizing a combination of feed, speed, and torque control) evolved due to inherent variation in constraint activity as a function of hole depth. A controller comparison study was conducted which demonstrates the advantages of this approach compared to (1) uncontrolled “conventional” drilling, (2) feed and speed controlled drilling, and (3) torque and speed controlled drilling. Benefits of reduced machining time, improved hole quality, and the elimination of tool breakage are demonstrated, and the potential economic impact is highlighted for an example production application.

Predictors of (non-) response in depressed outpatients treated with a three-phase sequential medication strategy

The predictive value of eight domains or sets of variables including sociodemographic aspects, premorbid history, symptomatology, personality, social and diagnostic data are evaluated in depressed outpatients with a Hamilton Rating Scale for Depression (HRSD) score of at least 14. Patients were treated using a three-phase sequential treatment strategy. Of the 119 patients, 88 completed the trial. The HRSD-score at the end of phases I, II or III was used as an outcome measure. Patients with an initially high HRSD-score and an obsessive-compulsive personality had a greater chance of recovery, while patients with somatization and a passive-aggressive personality had less of a chance of recovery. Variables involving psychiatric history, premorbid history or symptomatology of the depression, were not significantly related to outcome. The endogenous/non-endogenous distinction was not a predictor of response.

“Ralpha” Space Station plan takes flight

The anxiously awaited plans for a joint U.S.‐Russian space station were revealed by the Clinton Administration last week. Informally called “Ralpha,” the joint station would link the U.S.‐led space station “Alpha” with an upgraded Russian station (see Eos, October 26).The Clinton proposal lays out a threephase strategy for U.S.‐Russian cooperation in space, culminating in a “world” space station effort involving the United States, Russia, Japan, Canada, and Europe. The plan is described in an addendum to the “Program Implementation Plan” for Alpha.

Permutations on Illiac IV-Type Networks

Performing permutations of data on SIMD computers efficiently is important for high-speed execution of parallel algorithms. In this correspondence we consider realizing permutations such as perfect shuffle, matrix transpose, bit-reversal, the class of bit-permute- complement (BPC), the class of Omega, and inverse Omega permutations on N = 2n processors with Illiac IV-type interconnection network, where each processor is connected to processors at distances of ± 1 and ± N. The minimum number of data transfer operations required for realizing any of these permutations on such a network is shown to be 2(N − 1). We provide a general three-phase strategy for realizing permutations and derive routing algorithms for performing perfect shuffle, Omega, Inverse Omega, bit reversal, and matrix-transpose permutations in 2(N − 1) steps. Our approach is quite simple, and unlike previous approaches, makes efficient use of the topology of the Illiac IV-type network to realize these permutations using the optimum number of data transfers. Our strategy is quite powerful: any permutation can be realized using this strategy in 3(N − 1) steps.

The Tokamak: Model T Fusion Reactor

During the past several years there have been significant scientific and technological advances related to the tokamak magnetic confinement scheme. These are summarized in the context of a recent tokamak reactor design study which emphasizes reduced size, higher power density, and enhanced plant reliability and maintainability relative to earlier tokamak reactor design studies. The direct plant cost of the proposed reactor is estimated to be in the range $1000 to $1500 per electrical kilowatt. A three-phase strategy for demonstrating tokamak fusion power generation at a committed site is outlined. It is estimated that implementation of the three-phase program would require about 20 years and a total escalated expenditure $10 billion to $15 billion. The tokamak power plant described here is not viewed as definitive but rather as a point of departure in the development of a plan to demonstrate tokamak power generation.