Limited Number Of Values Research Articles

A Discrete Risk-Theory Approach to Manage Equity-Linked Policies in an Incomplete Market

We construct a model where, at each time instance, risky securities can only take a limited number of values and the equity-linked policy sold by the insurer to policyholders pays benefits linked to these securities. Since the number of states in the model exceeds the number of securities in the (incomplete) market, the martingale measure is not unique, posing a problem in pricing insurance instruments. In this framework, we consider how a super-replicating strategy violates the assumption of absence of arbitrage, yet simultaneously allows the insurance company to fully hedge against financial risk. Since the super-replicating strategy, when considered alone, would be too costly for any rational insured person, through the definition of the safety loading, we demonstrate how the insurer can still hedge against financial risk, albeit at the expense of increasing its exposure to demographic risk. This approach does not aim to show how the pricing of the index-linked policy can actually be performed but rather highlights how risk theory-based approaches (via the definition of the profit and loss random variable) enable the management of the trade-off between financial risk and demographic risk.

A Technique to Limit Hybrid Covert Channel Capacity via Random Increasing of Packets’ Lengths

Currently, due to the development and widespread use of communication systems, information security problems are very acute. Very often information leakage causes huge damage to both organizations and individuals. One of the mechanisms to organize information leakage during its transmission through communication channels is the construction of covert channels. Everywhere used packet networks provide huge opportunities for covert channels creating, which often leads to leakage of critical data. Packet length covert channels are resistant to traffic encryption, but there are some data transfer schemes that are difficult to detect. Therefore investigating of hybrid covert channel that uses both packet length and time is quite important. The purpose of this paper is to suggest a technique to protect data leakage via random increasing of packets’ lengths. The verification of the technique concerns with covert channel capacity examination depending on covert channel input parameters and countermeasure parameters. The authors have chosen the best scheme of a covert channel in terms of a residual covert channel capacity. The construction of covert channel shows that countermeasures applied don’t lead to errors. The main advantage of the scheme investigated is as follows: lengths of the transmitted packets take limited number of values that significantly increases the complexity of building such a channel and the ability to detect it.

PITFALLS IN CROSS‐SECTION STUDIES WITH INTEGRATED REGRESSORS: A SURVEY AND NEW DEVELOPMENTS

AbstractIn cross‐section studies, if the dependent variable is I(0) but the regressor is I(1), the true slope must be zero in the resulting “unbalanced regression.” A spuriously significant relationship may be found in large cross‐sections, however, if the integrated regressor is related to a stationary variable that enters the DGP but is omitted from the regression. The solution is to search for the related stationary variable, in some cases the first difference of the integrated regressor, in other cases, a categorical variable that can take on limited number of values which depend on the integrated variable. We present an extensive survey, new developments, and applications particularly in finance.

Critical objective function values in linear sum assignment problems

The linear sum assignment problem has been well studied in combinatorial optimization. Because of the integrality property, it is a linear programming problem with a variety of efficient algorithms to solve it. In the given research, we present a reformulation of the linear sum assignment problem and a Lagrangian relaxation algorithm for its reformulation. An important characteristic of the new Lagrangian relaxation method is that the optimal Lagrangian multiplier yields a critical bottleneck value. Lagrangian relaxation has only one Lagrangian multiplier, which can only take on a limited number of values, making the search for the optimal multiplier easy. The interpretation of the optimal Lagrangian parameter is that its value is equal to the price that must be paid for all objects in the problem to be assigned.

Study regarding the springback of metal sheet parts after bending

Plastic deformation of materials is accompanied by elastic deformation. After the bending process, the elastic deformation disappears and the part is changing its dimensions comparing with those of the tool. The change of bent part’s dimensions due to the elastic properties of material is called elastic springback . It influences the precision of bent parts, especially the bending angle, and this is why its value should be known in order to take the necessary measures in order to reduce or even annihilate its effects. Its value can be determined with analytical relations, from various nomograms or with experimental relations. Because the analytical relations offer results far from reality, this paper proposes a multivariable relation of springback (dependent variable) as a function of several independent variables obtained on the basis of experimental results, in real working conditions and using the method of regression functions. This method is based on simultaneous variation of considered variables, using a limited number of values in the experimentation domain. A split experimental program was used. The obtained relation is true for any combination of values for considered variables, but, from their variation domains, it can be obtained separately the effects of independent variables on dependent variables.

Micro‐architectural approach to the efficient employment of STTRAM cells in a microprocessor register file

In this paper, the authors propose two approaches that employ spin transfer torque random access memory (STTRAM) in the design of the register file, an important part of embedded processors. However, STTRAM suffers from both endurance and latency in the write operation. Consequently, employing STTRAM in the register file entails two challenges: (i) the lifetime significantly decreases as data are frequently written into a register file; (ii) the delay of the critical path increases as a result of the slow write operation. They have proposed using two well-known micro-architectural approaches: the last-write-update (LWU) and the value locality (VL), to minimize the number of write operations into a register. The main observation behind LWU is that only the last write operations of certain registers in the re-order buffer should be considered. VL exploits the fact that a limited number of values are more likely to be written into a register file. Their simulation shows that by employing the LWU and VL approaches, the lifetime of the STTRAM-based register file, compared with the lifetime of traditional static RAM-based register file architecture, extends to about 40 years on average and around 3.5 years in the worst case while improving power consumption by 30%.

A hybrid model using logistic regression and wavelet transformation to detect traffic incidents

This research paper investigates a hybrid model using logistic regression with a wavelet-based feature extraction for detecting traffic incidents. A logistic regression model is suitable when the outcome can take only a limited number of values. For traffic incident detection, the outcome is limited to only two values, the presence or absence of an incident. The logistic regression model used in this study is a generalized linear model (GLM) with a binomial response and a logit link function. This paper presents a framework to use logistic regression and wavelet-based feature extraction for traffic incident detection. It investigates the effect of preprocessing data on the performance of incident detection models. Results of this study indicate that logistic regression along with wavelet based feature extraction can be used effectively for incident detection by balancing the incident detection rate and the false alarm rate according to need. Logistic regression on raw data resulted in a maximum detection rate of 95.4% at the cost of 14.5% false alarm rate. Whereas the hybrid model achieved a maximum detection rate of 98.78% at the expense of 6.5% false alarm rate. Results indicate that the proposed approach is practical and efficient; with future improvements in the proposed technique, it will make an effective tool for traffic incident detection.

A New Semi-Lagrangean Relaxation for the K-Cardinality Assignment Problem

Recently Beltran-Royo, Vial & Alonso-Ayuso (2012) presented a semi-Lagrangean relaxation for the classical p-median location problem and for the incapacitated facility location problem. The results, obtained using the semi-Lagrangean relaxation approach, were quite impressive. In this paper we use a semi-Lagrangean relaxation to obtain an efficient solution method for the k-cardinality assignment problem. The method has only one semi-Lagrangean multiplier that can only take on a limited number of values, making the search for the optimal multiplier easy. Since the semi-Lagrangean relaxation closes the duality gap, this leads to an extremely reliable and easily implementable method for finding k-cardinality assignments in large-scale cases. The method is computationally tested on the examples commonly used in the literature.

A new Semi-Lagrangean Relaxation for the k-cardinality assignment problem

Recently Beltran-Royo, Vial & Alonso-Ayuso (2012) presented a semi-Lagrangean relaxation for the classical p-median location problem and for the incapacitated facility location problem. The results, obtained using the semi-Lagrangean relaxation approach, were quite impressive. In this paper we use a semi-Lagrangean relaxation to obtain an efficient solution method for the k-cardinality assignment problem. The method has only one semi-Lagrangean multiplier that can only take on a limited number of values, making the search for the optimal multiplier easy. Since the semi-Lagrangean relaxation closes the duality gap, this leads to an extremely reliable and easily implementable method for finding k-cardinality assignments in large-scale cases. The method is computationally tested on test examples commonly used in the literature.

Effects of personal values on customer satisfaction

PurposeDifferent authors suggest that personal values (as opposed to economic values of objects) are important antecedents of service satisfaction. This paper seeks to investigate empirically two specific processes that relate personal values to satisfaction with (financial) services (the value percept disparity model and the (value) disconfirmation model).Design/methodology/approachThe paper generalizes both models into a new value disparity‐disconfirmation model, providing testable conditions to evaluate and compare the validity of the original models. The paper specifies the model in terms of hierarchical linear models and assesses their empirical fit with data on 18 bank branches.FindingsThe results of the study best support the value disconfirmation model. Furthermore, the paper shows that in the research's setting of a financial service provider the external dimension of values is more instrumental in predicting satisfaction than the internal dimension.Research limitations/implicationsSince only a single service setting has been studied and a limited number of values have been focused on at one particular moment in time, the authors are hesitant to generalize the results beyond the scope of this study.Practical implicationsEmployee values are clearly associated with customer satisfaction. In fact, irrespective of their own values, customers do not seem to appreciate it when employees have values that differ from their own. Moreover, external values are more important than internal values in explaining satisfaction.Originality/valueThe paper is an empirical test of which model (the value percept disparity model or the value disconfirmation model) is better in explaining customer satisfaction, thereby providing conceptual clarity, theoretical parsimony and practical implications of the impact of personal values on satisfaction.

Decoding Algorithms for Nonbinary LDPC Codes Over GF$(q)$

In this letter, we address the problem of decoding nonbinary low-density parity-check (LDPC) codes over finite fields GF(q), with reasonable complexity and good performance. In the first part of the letter, we recall the original belief propagation (BP) decoding algorithm and its Fourier domain implementation. We show that the use of tensor notations for the messages is very convenient for the algorithm description and understanding. In the second part of the letter, we introduce a simplified decoder which is inspired by the min-sum decoder for binary LDPC codes. We called this decoder extended min-sum (EMS). We show that it is possible to greatly reduce the computational complexity of the check-node processing by computing approximate reliability measures with a limited number of values in a message. By choosing appropriate correction factors or offsets, we show that the EMS decoder performance is quite good, and in some cases better than the regular BP decoder. The optimal values of the factor and offset correction are obtained asymptotically with simulated density evolution. Our simulations on ultra-sparse codes over very-high-order fields show that nonbinary LDPC codes are promising for applications which require low frame-error rates for small or moderate codeword lengths. The EMS decoder is a good candidate for practical hardware implementations of such codes

Assessing multiple sclerosis activity: is the in vitro production of tumor necrosis factor-alpha, interleukins 2, 6, 4, and 10, and immunoglobulin G of value?

Tumor necrosis factor (TNF) alpha, interleukins (IL) 2, 4, 6, and 10, and IgG oligoclonal bands (IgG OB) in vitro production was assessed, after whole-blood stimulation with lipopolysaccharide or concanavalin A, in 61 patients presenting with relapsing-remitting, relapsing-progressive, or chronic progressive multiple sclerosis. Multiple sclerosis patients were receiving no treatment or azathioprine (AZA), cyclosporin, cyclophosphamide, subcutaneous interferon (IFN) beta 1 a, or corticosteroids (CST). Statistical correlations significantly showed that: (a) AZA lowers TNF-alpha (P = 0.002) and increases IL-4 production (P = 0.0024), and IFN-beta 1 a increases TNF-alpha and decreases IL-4 levels; (b) CST has a negative effect on TNF-alpha, IL-6, and IL-4 synthesis; and (c) AZA, IFN-beta 1 a, and CST diminish IgG OB synthesis (P = 0.001). Although our study of the dynamics of TNF-alpha, IL-2, IL-4, IL-6, and IL-10 in vitro production generally found no statistically significant correlations (partly explained by the limited number of values in the various groups), IL-6 was shown to drop during the periods surrounding relapse (P = 0.05) in the absence of treatment, while TNF-alpha (P = 0.04) and IL-6 (P < 0.05) dropped before exacerbation in the presence of AZA. In vitro production of TNF-alpha was closely and positively correlated with that of IL-6, independently of clinical features. The enhanced production of IL-10 detected before or at relapse with AZA and IFN-beta 1 a (trends) may interfere with initiation of the immune reaction and with the development of new CNS lesions. Some discrepancies with previously published results stress the difficulties in studying the state of stimulation of different populations of leukocytes by using a variety of in vitro stimuli and in establishing a correlation between mRNA studies and the amount of final or active protein produced.

Partial texture analysis by the modified maximum entropy method

The orientation distribution function (ODF), being a continuous function of three variables, requires a large number of values or series coefficients for its complete description. A partial texture analysis, using a fixed angle texture analyzer, i.e., less pole figure data, gives a limited number of values of the texture function, i.e., an approximate ODF. This partial texture analysis is very important both for theory and for its application to on-line texture analysis, used to refine a manufacturing process and optimize materials properties. Quite recently, the modified maximum entropy method (MMEM), which improved the primary maximum entropy method with series coefficients as constraints, introduced the maximum entropy principle directly into the least square equation of pole figure inversion proposed by Bunge. Because the positivity condition is automatically satisfied, less data are needed to obtain an accurate solution with the MMEM. In the present paper, the MMEM is used of find the partial ODF from only a few data measured on the pole figure. The validity of the new algorithm will be proved by the partial ODF analysis of cold-rolled copper sheets with moderate-to-strong textures.

5168231 NMR imaging device, method for correcting inhomogeneity and method for making magnets used in this device

Inhomogeneities in a magnetic field are corrected by means of openings of square or polygonal cross-section in the periphery of the magnet. Permanent magnets required for obtaining the desired correction are lodged in the openings. Thus, the orientation of the permanent magnets can only assume a limited number of values, which simplifies the calculation to determine the positions of the magnets used to correct the inhomogeneity of the magnetic field. It is mainly applicable to the correction of inhomogeneity of the magnetic field of a magnet used in nuclear magnetic resonance imaging.

Partial Texture Analysis

The texture is the orientation distribution function of the crystallites of a polycrystalline sample. Being a continuous function of three variables, it requires a large number of values for its complete description. The texture can be expressed in terms of a series expansion. It then requires a large number of coefficients for its complete description. When all functional values or all coefficients are determined from experimental measurements we speak of complete texture analysis. The most important methods for complete texture analysis are individual orientation measurements of a large number of crystals and pole figure measurement followed by pole figure inversion.If only a limited number of values of the texture function or a few of its coefficients are being determined we speak of “partial texture analysis”. The most important methods of partial texture analysis are the fixed angle texture analyzer and the measurement of the anisotropy of physical properties such as Young′s modulus magnetic properties, thermal expansion and others.