Hypothetical Problem Research Articles

Emerging technologies in artificial intelligence: quantum rule-based systems

This article tries to establish synergies between two areas of research and development that are apparently disconnected: artificial intelligence (AI) and quantum computing (QC). The article begins with a brief description of the origins of AI and the type of problems that AI tries to solve. Next, we focus on a specific type of AI program, the so-called rule-based system (RBS). In this regard, one of the biggest problems with RBS is the pattern-matching that is related to the process of rule selection. This makes RBS very sensitive to the size of the problem and to changing environments, which is at the core of a very significant increase in computational cost. In this context we wonder if the use of QC techniques could help solve the problem. We have already presented ideas and concepts in the quantum world that could contribute to improving the performance of RBS. We place special emphasis on the principle of coherent superposition, on the intrinsically parallel character of QC, on the probabilistic nature of QC, and we describe some quantum operators that, of course, must be reversible. Next, we build a quantum architecture equivalent to a conventional inferential circuit and analyze the results. The article continues with the construction of a quantum rule-based system that solves a hypothetical problem in the field of medicine. Finally, the proposed approach is discussed, and preliminary conclusions are established.

Depression with and without preceding life event: Differential recognition and professional help-seeking inclination in youth?

Background: Low rates of professional help seeking for depression by youth is a well known global challenge. The study aimed at examining whether there might be differences in the rates of recognition of a hypothetical problem as a mental health problem when depressive symptoms are depicted as occurring in the context of a negative life event as compared to when these symptoms are depicted as occurring without any negative life event. The relationship between recognition as a mental health problem and help-seeking inclination from mental health professionals was also examined. Methods: Three hundred college youths within 18–25 years of age range formed the sample. Two vignettes describing moderate depression were used for all the participants. These two vignettes had identical content except that one of these mentioned a negative life event preceding the onset of depression. Each of these vignettes was followed by items to elicit recognition of the problem and inclination to seek help from mental health professionals if one was experiencing a similar problem. Results: Depressive symptoms arising in the context of a negative life event were less likely to be labeled as mental health problem and also less likely to be identified as depression. Accurate recognition of the problem as a mental health problem went hand in hand with significantly higher inclination to seek help from mental health professionals, but this was evident only in the vignette describing depressive symptoms without negative life event. Conclusion: The findings have implications for further research and for designing programs to improve help seeking for depression in Indian youth.

Trainees Looking Through the Lens of a Supervisor: Remediation and Gatekeeping Responses to Hypothetical Problems of Professional Competency

ABSTRACTThis study investigated MFT trainees' perspectives of competency problems as they imagine themselves as supervisors. Trainees read seven vignettes and selected from 17 remediation responses (N = 21) originally designed for licensed supervisors (Russell, Beggs, Peterson, & Anderson, 2007). Consistent with the literature, respondents endorsed talking with the trainee as their first line of remediation and reserved dismissal for competencies related to dishonesty/fraud. Contrary to past research, trainees identified late case notes as a dismissible offense and were more lenient with untreated mental illness. Supervisors might consider orienting trainees to ethical decision making and remediation policies/strategies prior to their work in the field.

Multi-criteria optimization strategies for tree-structured production chains

The aim of this paper is presentation of some optimization strategies applicable in the optimization of multi-stage and multi-thread chain structures (linear and tree-structured acyclic graphs) with multiple intermediate goal functions. The inspirations for this type of analysis are production chains often seen in industrial plants. Production in these plants consists of sequences of multiple units connected linearly or in tree-structured graphs in which, at various production stages, intermediate quality criteria, related to the semi-products, may have to be considered. Optimization strategies as well as the results of their application for different hypothetical problems and the real metallurgical problem of lead production are presented.

A new decision-making approach for multiple criteria sorting with an imbalanced set of assignment examples

We propose a novel approach to address a multiple criteria sorting (MCS) problem with an imbalanced set of assignment examples. The approach employs a piecewise-linear additive value function as the preference model and adopts the disaggregation–aggregation paradigm to infer a sorting model from provided assignment examples on a set of reference alternatives. We utilize a hierarchical clustering algorithm and several linear programming models to identify reference alternatives that are active to develop the sorting model, so that inactive ones are eliminated from the whole set of reference alternatives. Then, in order to construct a balanced set of assignment examples, a balancing algorithm is proposed to balance active reference alternatives across categories. Finally, the sorting model is obtained by minimizing the sum of violations between values of active reference alternatives and corresponding category thresholds. Furthermore, the performance of the proposed approach is investigated on a hypothetical problem and several real data sets. The experimental results show that our approach is efficient to address the MCS problem with an imbalanced set of assignment examples.

The risks of extreme load extrapolation

Abstract. An important problem in wind turbine design is the prediction of the 50-year load, as set by the IEC 61400-1 Design Load Case (DLC) 1.1. In most cases, designers work with limited simulation budgets and are forced to use extrapolation schemes to obtain the required return level. That this is no easy task is proven by the many studies dedicated to finding the best distribution and fitting method to capture the extreme load behavior as well as possible. However, the issue that is often overlooked is the effect that the sheer uncertainty around the 50-year load has on a design process. In this paper, we use a collection of 96 years' worth of extreme loads to perform a large number of hypothetical design problems. The results show that, even with sample sizes exceeding N = 103 10 min extremes, designs are often falsely rejected or falsely accepted based on an over- or underpredicted 50-year load. Therefore, designers are advised to be critical of the outcome of DLC 1.1 and should be prepared to invest in large sample sizes.

A REVIEW ON ENERGY EFFICIENT JOB SCHEDULING ALGORITHMS IN GREEN CLOUD COMPUTING

Cloud computing is the hottest topic in today’s world and is being used by most of the information technology companies due to its benefits incost saving and ease of use. It is a dynamic, scalable, and pay-per-use distributed computing model. The cloud computing is aims to give accessto remote and geographically distributed resources. Scheduling the job from one data center to other data center or from one region of cloud toother region is truly a testing in cloud environment. However, when data are shifted from one data center to other data center, huge amount ofcarbon dioxide (CO2) gases emits and also consumes more power. Since energy is an important issue, that is, why green cloud computing comesinto the picture. Green cloud computing can be obtained by applying various techniques and algorithms, which use less power and emits lessCO2 gas, that is, damaging the environment. Cloud provides many facilities to its tenants such as sharing of resources for different purposes. Incloud domain, job scheduling is one of the biggest and hypothetical problems. Numerous investigations for scheduling a job and efforts carriedout in this regard because it is one of the main jobs to get the most profit. Scheduling can decrease the power consumption. So many algorithmshad been proposed for this purpose, and a lot more had to be done. In the paper, intends to present a variety of energy-efficient job schedulingalgorithms along with performance comparison analysis of various preexisting algorithms for scheduling jobs to provide energy efficiency ingreen cloud computing.

Material flow optimisation in a multi-echelon and multi-product supply chain

This paper addresses a distribution problem in a multi-product, multi-echelon supply chain. We develop a mixed integer linear programming formulation that considers allocation of vehicles with varying capacities for the transportation of products between the stages of the supply chain. The cost of transportation includes the fixed and variable costs of using the vehicles. The proposed formulations are solved optimally up to certain sizes, and we propose a heuristic based on total opportunity penalty cost method to solve the large sized problems. These proposed solution procedure is tested over a set of hypothetical problem sets. The results indicate that the proposed heuristic algorithm yields solutions within 5% from the optimal solutions.

Material flow optimisation in a multi-echelon and multi-product supply chain

This paper addresses a distribution problem in a multi-product, multi-echelon supply chain. We develop a mixed integer linear programming formulation that considers allocation of vehicles with varying capacities for the transportation of products between the stages of the supply chain. The cost of transportation includes the fixed and variable costs of using the vehicles. The proposed formulations are solved optimally up to certain sizes, and we propose a heuristic based on total opportunity penalty cost method to solve the large sized problems. These proposed solution procedure is tested over a set of hypothetical problem sets. The results indicate that the proposed heuristic algorithm yields solutions within 5% from the optimal solutions.

Bayesian Networks Improve Causal Environmental Assessments for Evidence-Based Policy.

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on valued ecological resources. These aspects are demonstrated through hypothetical problem scenarios that explore some major benefits of using Bayesian networks for reasoning and making inferences in evidence-based policy.

Investigation of the groundwater modelling component of the Integrated Water Flow Model (IWFM)

ABSTRACTThe Integrated Water Flow Model (IWFM), developed by the California Department of Water Resources, is an integrated hydrological model that simulates key flow processes including groundwater flows, streamflow, stream–aquifer interactions, rainfall–runoff and infiltration. It also simulates the agricultural water demand as a function of soil, crop and climatic characteristics, as well as irrigation practices, and allows the user to meet these demands through pumping and stream diversions. This study investigates the modelling performance of the groundwater module of IWFM using several hypothetical test problems that cover a wide range of settings and boundary conditions, by comparing the simulation results with analytical solutions, field and laboratory observations, or with results from MODFLOW outputs. The comparisons demonstrate that IWFM is capable of simulating various hydrological processes reliably.EDITOR M.C. Acreman; ASSOCIATE EDITOR A. Efstratiadis

Inexact fuzzy integer chance constraint programming approach for noise control within an urban environment

This article introduces an inexact fuzzy integer chance constraint programming (IFICCP) approach for identifying noise reduction strategy under uncertainty. The IFICCP method integrates the interval programming and fuzzy chance constraint programming approaches into a framework, which is able to deal with uncertainties expressed as intervals and fuzziness. The proposed IFICCP model can be converted into two deterministic submodels corresponding to the optimistic and pessimistic conditions. The modelling approach is applied to a hypothetical control measure selection problem for noise reduction. Results of the case study indicate that useful solutions for noise control practices can be acquired. Three acceptable noise levels for two communities are considered. For each acceptable noise level, several decision alternatives have been obtained and analysed under different fuzzy confidence levels, which reflect the trade-offs between environmental and economic considerations.

A semi-analytical method and its application for calculating the thermal stress and displacement of sparsely fractured rocks with water flow and heat transfer

Using Goodier’s thermo-elastic displacement potential and Laplace transform, a semi-analytical method is developed for calculating the displacement and stress induced by heat transfer in sparsely fractured granitic rocks with saturated water flow and distributed heat sources. An integral equation of the thermo-elastic displacement potential is formulated in the Laplace-transformed domain. The fractures are discretized into rectangular elements, and the elemental integrals that involve singularities are calculated analytically. The numerical solutions of the potential are calculated using numerical Laplace inversion, and the temperature-gradient-induced displacements and stresses are calculated using central differences. The method is employed to examine the characteristics of the temperature-gradient-induced displacement and stress for a hypothetical problem that is intended to mimic the near-field environment of deep geological repositories of high-level radioactive wastes. Among other things, the results reveal the following: (1) In early time of operation of the repository, the region of rock under thermal expansion and compressive is limited; (2) As the intensity of the heat source gets smaller with time, only a small portion of the rock expands whereas the remaining portion contracts; (3) Downstream peak temperatures may be higher due to the supply of thermal energy by the water-flow-facilitated heat transfer, and patterns of influences of the water velocities on the thermal stress and displacement are similar; (4) Sufficiently close heat sources would cause superposition of the heating effects and make the near-field temperature increase significantly.

An upscaled approach for transport in media with extended tailing due to back-diffusion using analytical and numerical solutions of the advection dispersion equation

The mono-continuum advection-dispersion equation (mADE) is commonly regarded as unsuitable for application to media that exhibit rapid breakthrough and extended tailing associated with diffusion between high and low permeability regions. This paper demonstrates that the mADE can be successfully used to model such conditions if certain issues are addressed. First, since hydrodynamic dispersion, unlike molecular diffusion, cannot occur upstream of the contaminant source, models must be formulated to prevent “back-dispersion.” Second, large variations in aquifer permeability will result in differences between volume-weighted average concentration (resident concentration) and flow-weighted average concentration (flux concentration). Water samples taken from wells may be regarded as flux concentrations, while soil samples may be analyzed to determine resident concentrations. While the mADE is usually derived in terms of resident concentration, it is known that a mADE of the same mathematical form may be written in terms of flux concentration. However, when solving the latter, the mathematical transformation of a flux boundary condition applied to the resident mADE becomes a concentration type boundary condition for the flux mADE. Initial conditions must also be consistent with the form of the mADE that is to be solved. Thus, careful attention must be given to the type of concentration data that is available, whether resident or flux concentrations are to be simulated, and to boundary and initial conditions. We present 3-D analytical solutions for resident and flux concentrations, discuss methods of solving numerical models to obtain resident and flux concentrations, and compare results for hypothetical problems. We also present an upscaling method for computing “effective” dispersivities and other mADE model parameters in terms of physically meaningful parameters in a diffusion-limited mobile–immobile model. Application of the latter to previously published studies of systems that exhibit early breakthrough and extended tailing shows that the upscaled mADE model is able to describe the observed behavior with reasonable accuracy given only known physical parameters for the systems without any model calibration.

An Application of Nash Bargaining to Intellectual Property Negotiations

In what follows we propose a solution to a hypothetical bargaining problem that is likely to arise when the owner of an invention, which is assumed to lower the marginal cost of production, negotiates a patent license with producers. We show that, under various assumptions about the downstream market structure, the solution that maximizes the Nash product in a specific market context need not require an even split of the available surplus. This conclusion about the equilibrium allocation of surplus is appropriate whether one adopts the original axiomatic treatment by Nash or the later dynamic non-cooperative bargaining model of Rubinstein and others. Initially, we describe the use of the Nash solution when there is a single patentee negotiating a license with a monopolist producer. We subsequently describe the more-recent Nash-in-Nash bargaining solution of Horn and Wolinsky, assuming there are two downstream rival producers with market power who independently negotiate a non-exclusive license with the patentee. Throughout, we pay particular attention to the complexities of defining disagreement payoffs, properly including attention to their credibility in the sense of Binmore.

Can Singularity Problem in Economics be solved by Omnipotent Mathematics?

In mathematics, singularity signifies a point at which a given mathematical function or its derivatives is not defined. Singularities are mostly mathematical that occur in the mathematical models describing physical systems. In social science compared to physical science, fewer cases of singularity arise, among which the mostly discussed one is technological singularity. Omnipotent mathematics (OM) is an approach to analyze singularity in a mathematical framework. In this approach “zero” is a non-existent entity which decomposes into quasi-existent entities, which in turn interact with each other to generate an existent entity. The focus of this paper is to address a typical hypothetical singularity problem in economics and try to solve it using omnipotent mathematics. Here the economic input-output model has been used to showcase an economic singularity problem that can be resolved in terms of quasi-existent entity.

Impact of Rewards on Job Satisfaction Evidences from Ttelecom Sector of Pakistan

Organizations today need to create a set up at workplace that makes the employees motivated, loyal, satisfied and committed for a strategic competence. Effective organizational intervention leads to greater satisfaction of the employees if they are provided rewards and extrinsic compensation like pay increments, bonuses, allowances and grants along with job security and promotion opportunities. The employees feel satisfied and psychologically affiliated with their organizations if they found that their organizations value and reward their efforts which in turn serve as the competitive advantage in the long run. The present study is an effort to investigate the impact of extrinsic rewards on job satisfaction in a telecom sector. The study examined the effect of extrinsic rewards such as salary, bonuses and benefits to know the level of employee’s job satisfaction. The study was conducted in a telecom sector in the region of Islamabad. Huawei International (Pvt.) Ltd is a well reputed organization in telecom sector. The data was collected from 125 employees of different organizational levels including executives like directors, senior managers, middle managers and low level staff through self administered questionnaires composed of 15 questions. 100 out of 125 employees belonging to different categories responded. Two hypothetical problems were taken into consideration and tested using SPSS software. Analysis of data received in the form of employee response, was also made using SPSS. Results nullified an initial or null hypothesis and then alternative hypothesis when tested, showed positive trends in all variables. Impact of rewards showed its importance at a higher level of relationship. The results of regression analysis show that job satisfaction is more dependent on extrinsic rewards. The managerial implications, limitation of the study, future guidelines and recommendations have also been given.

Thomas–Fermi model for a bulk self-gravitating stellar object in two dimensions

In this article we have solved a hypothetical problem related to the stability and gross properties of two-dimensional self-gravitating stellar objects using the Thomas–Fermi model. The formalism presented here is an extension of the standard three-dimensional problem discussed in the book on statistical physics, Part I by Landau and Lifshitz. Further, the formalism presented in this article may be considered a class problem for post-graduate-level students of physics or may be assigned as a part of their dissertation project.

Rocks and other hard places: tracing ethical thinking in Korean and English dialog

Researchers into moral education, and ethics educators too, often find themselves between a rock and a hard place. On the one hand, we wish to know what the child will do beyond the narrow range of communicative functions carried out in a classroom, and to do this, we employ purely hypothetical problems, that is, problems that from the child's point of view are constructed merely of language. On the other hand, we find that when we construct hypothetical problems out of language, the child's response is likewise merely constructed of language. Our solution is to turn this problem into a postulate: we take ‘mere language’ as the object of ethical study and construe grammar as a chain of choices, many with moral implications. Therefore, for example, issuing imperatives implies a different ethical stance from creating interrogatives, and both are different again from sharing information with declaratives; so too, presenting an experience as a doing involves being answerable for the deed in a way that is different from presenting it as a happening. We offer a modest demonstration of how this approach could be used in research in language and education.

Uncle Jack, Jaycee and the equitable doctrine of estoppel: using Second Life to support the development of advanced oral communication skills in law students

The ability to communicate appropriately, effectively and persuasively to a diverse audience is a mandated learning outcome for all Australian law students. Communication skills include both written and oral skills. This article examines and evaluates a project aimed at reconceptualising and, thereby, expanding the learning and teaching of oral communication skills in law through the digital presentation of a hypothetical problem using Second Life.