The impact of ownership structure on corporate debt policy : two stage least square simultaneous model approach for post crisis period : evidence from Kuala Lumpur Stock Exchange

Ownership concentration as a governance mechanism has received considerable attention among academician, practitioners as well as policy makers because large-block shareholders are increasingly active in their demands that corporations adopt effective governance mechanisms to control managerial decisions, which include corporate debt policy. Earlier study on the agency model of the firm widely recognizes that the managerial ownership and external debt play an important role in mitigating agency conflicts and enhancing firm value. They also found that increase in the external monitors, for example the institutional investors, can actually play a useful role in limiting agency problems in the firm. This paper, using 100 Composite Index companies from Brusa Malaysia between 1998 to 2002 explores the impact of institutional holdings on managerial ownership and debt policy in an integrated framework by using a simultaneous equations estimation procedure (2SLS). The findings show that there is a significant impact of institutional ownership which serves effective control mechanism on managerial ownership and corporate debt policy as hypothesized. Findings of such evidence suggest that institutional holding thus have played an important role in managers' strategic management decision and reduce agency conflict. In addition, corporate debt policy too is governed by managerial ownership and exhibited a negative relation.

A novel monotonic fixed-point algorithm for l1-regularized least square vector and matrix problem

Least square problem with l₁ regularization has been proposed as a promising method for sparse signal reconstruction (e.g., basis pursuit de-noising and compressed sensing) and feature selection (e.g., the Lasso algorithm) in signal processing, statistics, and related fields. These problems can be cast as l₁-regularized least-square program (LSP). In this paper, we propose a novel monotonic fixed point method to solve large-scale l₁-regularized LSP. And we also prove the stability and convergence of the proposed method. Furthermore we generalize this method to least square matrix problem and apply it in nonnegative matrix factorization (NMF). The method is illustrated on sparse signal reconstruction, partner recognition and blind source separation problems, and the method tends to convergent faster and sparser than other l₁-regularized algorithms.

Rapid determination of protein contents in microencapsulated fish oil supplements by ATR-FTIR spectroscopy and partial least square regression (PLSR) analysis

Following the recent success in quantitative analysis of essential fatty acid compositions in a commercial microencapsulated fish oil (?EFO) supplement, we extended the application of portable attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic technique and partial least square regression (PLSR) analysis for rapid determination of total protein contents-the other major component in most commercial ?EFO powders. In contrast to the traditional chromatographic methodology used in a routine amino acid analysis (AAA), the ATR-FTIR spectra of the ?EFO powder can be acquired directly from its original powder form with no requirement of any sample preparation, making the technique exceptionally fast, noninvasive, and environmentally friendly as well as being cost effective and hence eminently suitable for routine use by industry. By optimizing the spectral region of interest and number of latent factors through the developed PLSR strategy, a good linear calibration model was produced as indicated by an excellent value of coefficient of determination R2 = 0.9975, using standard ?EFO powders with total protein contents in the range of 140-450 mg/g. The prediction of the protein contents acquired from an independent validation set through the optimized PLSR model was highly accurate as evidenced through (1) a good linear fitting (R2 = 0.9759) in the plot of predicted versus reference values, which were obtained from a standard AAA method, (2) lowest root mean square error of prediction (11.64 mg/g), and (3) high residual predictive deviation (6.83) ranked in very good level of predictive quality indicating high robustness and good predictive performance of the achieved PLSR calibration model. The study therefore demonstrated the potential application of the portable ATR-FTIR technique when used together with PLSR analysis for rapid online monitoring of the two major components (i.e., oil and protein contents) in finished ?EFO powders in the actual manufacturing setting.

Improving the performance of the LMS and RLS algorithms for adaptive equalizer

In this paper, we present the experiment results of three adaptive equalization algorithms: least-mean-square (LMS) algorithm, discrete cosine transform-least mean square (DCT-LMS) algorithm, and recursive least square (RLS) algorithm. Based on the experiments, we obtained that the convergence rate of LMS is slow; the convergence rate of RLS is great faster while the computational price is expensive; the performance of that two parameters of DCT-LMS are between the previous two algorithms, but still not good enough. Therefore we will propose an algorithm based on H2 in a coming paper to solve the problems.

Conversion of the hot torsion test results into flow curve with multiple regimes of hardening

The method of Fields and Backofen has been commonly used to reduce the data obtained by hot torsion test into flow curves. The method, however, is most suitable for materials with monotonic strain hardening behaviour. Other methods such as Stüwe’s method, tubular specimens, differential testing and the inverse method, each suffer from similar drawbacks. It is shown in the current work that for materials with multiple regimes of hardening any method based on an assumption of constant hardening indices introduces some errors into the flow curve obtained from the hot torsion test. Therefore such methods do not enable accurate prediction of onset of recrystallisation where slow softening occurs. A new method to convert results from the hot torsion test into flow curves by taking into account the variation of constitutive parameters during deformation is presented. The method represents the torque twist data by a parametric linear least square model in which Euler and hyperbolic coefficients are used as the parameters. A closed form relationship obtained from the mathematical representation of the data is employed next for flow stress determination. Two different solution strategies, the method of normal equations and singular value decomposition, were used for parametric modelling of the data with hyperbolic basis functions. The performance of both methods is compared. Experimental data obtained by FHTTM, a flexible hot torsion test machine developed at IROST, for a C–Mn austenitic steel was used to demonstrate the method. The results were compared with those obtained using constant strain and strain rate hardening characteristics.

The influence of strategic HRM and sector on perceived performance in health services organizations

In this study, we examine a variety of management characteristics of for-profit and not-for-profit organizations in the health services (HS) industry. Data collected from Australian senior executives are used to test the relationships between managerial constructs such as employee commitment, customer demandingness, strategic HRM orientation and the adoption of human capital-enhancing human resource (HR) practices and perceived overall performance. Data analysis conducted using the Partial Least Square Modeling show a statistically significant path from commitment to employees, customer demandingness and strategic HRM orientation to the adoption of human capital-enhancing HR practices (such as selective staffing, comprehensive training, and performance appraisal) to perceived organizational performance. The results also show that private sector health service organizations have a higher level of perceived performance.

Minimal force jump within human and assistive robot cooperation

When an assistant robotic manipulator cooperatively performs a task with a human and the task is required to be highly reliable, then fault tolerance is essential. To achieve the fault tolerance force within the human robot cooperation, it is required to map the effects of the faulty joint of the robot into the manipulator’s healthy joints’ torque space and the human force. The objective is to optimally maintain the cooperative force within the human robot cooperation. This paper aims to analyze the fault tolerant force within the cooperation and two frameworks are proposed. Then they have been validated through a fault scenario. Finally, the minimum force jump which is the optimal fault tolerance has been achieved.

Low complexity MMSE based channel estimation technique for LTE OFDMA systems

Long term evolution (LTE) is designed for high speed data rate, higher spectral efficiency, and lower latency as well as high-capacity voice support. LTE uses single carrierfrequency division multiple access (SC-FDMA) scheme for the uplink transmission and orthogonal frequency division multiple access (OFDMA) in downlink. The one of the most important challenges for a terminal implementation are channel estimation (CE) and equalization. In this paper, a minimum mean square error (MMSE) based channel estimator is proposed for an OFDMA systems that can avoid the ill-conditioned least square (LS) problem with lower computational complexity. This channel estimation technique uses knowledge of channel properties to estimate the unknown channel transfer function at non-pilot subcarriers.

Modelling for injection moulding process based on principal component regression method

Determination of the optimal operating condition for moulding process has been of special interest for many researchers. To determine the optimal setting, one has to derive the model of injection moulding process first which is able to map the relationship between the input process control factors and output responses. One of most popular modeling techniques is the linear least square regression due to its effectiveness and completeness. However, the least square regression was found to be very sensitive to the outliers and failed to provide a reliable model if the control variables are highly related with each other. To address this problem, a new modeling method based on principal component regression was proposed in this paper. The distinguished feature of our proposed method is it does not only consider the variance of covariance matrix of control variables but also consider the correlation coefficient between control variables and target variables to be optimised. Such a modelling method has been implemented into a commercial optimisation software and field test results demonstrated the performance of the proposed modelling method.

Channel estimation scheme for 3.9G wireless communication systems using RLS algorithm

Main challenges for a terminal implementation are efficient realization of the receiver, especially for channel estimation (CE) and equalization. In this paper, training based recursive least square (RLS) channel estimator technique is presented for a long term evolution (LTE) single carrier-frequency division multiple access (SC-FDMA) wireless communication system. This CE scheme uses adaptive RLS estimator which is able to update parameters of the estimator continuously, so that knowledge of channel and noise statistics are not required. Simulation results show that the RLS CE scheme with 500 Hz Doppler frequency has 3 dB better performances compared with 1.5 kHz Doppler frequency.

Reproductive consequences of male arrival order in the Bark beetle, Ips grandicollis

The ability of birds to perceive, assess and appropriately respond to the presence of relatively novel threats is important to their survival. We hypothesized that the cognitive capacity of birds will influence their ability for accurate response to novelty. We used brain volume as a surrogate for cognitive capacity and postulated that larger brained birds would moderate their responses when presented with a benign, frequently occurring stimulus, such as a person, because they would habituate more readily. We conducted phylogenetic generalized least square regression to investigate the relationship between brain volume and flight initiation distance (FID; the distance to which a bird can be approached before initiating escape behaviour), while controlling for confounding factors including body size (body mass and wing length) and migration status. We compared seven different models using combinations of these parameters using Akaike's information criterion to determine the best approximating model(s) explaining FID. The two best-supported models included only wing length and only body mass with Akaike weights of 0.396 and 0.311 respectively. No model including brain volume had an Akaike weight greater than 0.083 and brain volume was poorly correlated with FID in models after controlling for body mass. Thus, brain volume does not appear to strongly relate to bravery among these shorebirds.

Quantitative determination of fatty acid compositions in micro-encapsulated fish-oil supplements using Fourier transform infrared (FTIR) spectroscopy

The research describes a rapid method for the determination of fatty acid (FA) contents in a micro-encapsulated fish-oil (μEFO) supplement by using attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic technique and partial least square regression (PLSR) analysis. Using the ATR-FTIR technique, the μEFO powder samples can be directly analysed without any pre-treatment required, and our developed PLSR strategic approach based on the acquired spectral data led to production of a good linear calibration with R^₂ = 0.99. In addition, the subsequent predictions acquired from an independent validation set for the target FA compositions (i.e., total oil, total omega-3 fatty acids, EPA and DHA) were highly accurate when compared to the actual values obtained from standard GC-based technique, with plots between predicted versus actual values resulting in excellent linear fitting (R² ⩾ 0.96) in all cases. The study therefore demonstrated not only the substantial advantage of the ATR-FTIR technique in terms of rapidness and cost effectiveness, but also its potential application as a rapid, potentially automated, online monitoring technique for the routine analysis of FA composition in industrial processes when used together with the multivariate.

Brains and bravery: little evidence of a relationship between brain size and flightiness in shorebirds

The ability of birds to perceive, assess and appropriately respond to the presence of relatively novel threats is important to their survival. We hypothesized that the cognitive capacity of birds will influence their ability for accurate response to novelty. We used brain volume as a surrogate for cognitive capacity and postulated that larger brained birds would moderate their responses when presented with a benign, frequently occurring stimulus, such as a person, because they would habituate more readily. We conducted phylogenetic generalized least square regression to investigate the relationship between brain volume and flight initiation distance (FID; the distance to which a bird can be approached before initiating escape behaviour), while controlling for confounding factors including body size (body mass and wing length) and migration status. We compared seven different models using combinations of these parameters using Akaike's information criterion to determine the best approximating model(s) explaining FID. The two best-supported models included only wing length and only body mass with Akaike weights of 0.396 and 0.311 respectively. No model including brain volume had an Akaike weight greater than 0.083 and brain volume was poorly correlated with FID in models after controlling for body mass. Thus, brain volume does not appear to strongly relate to bravery among these shorebirds.

The value of executive director share ownership and discretionary accruals

Purpose – The purpose of this paper is to investigate the relation between the value of executive director share ownership and discretionary accruals.

Design/methodology/approach – This study uses a dataset of 1,173 firm-year observations drawn from 188 Australian listed companies for the period 2000-2006. The analysis is based on multivariate regression analysis and ordinary least square models were used to investigate the relation between the value of managerial ownership and discretionary accruals. The issue of potential endogeneity is addressed by using a simultaneous equation system.

Findings – A negative relation is found between value of managerial share ownership and discretionary accruals at lower levels of value of ownership, which is consistent with the theorised incentive alignment that as the managers commit more resources to their firms, stakeholders impose less contractual constraints specified in terms of accounting numbers and managers make lower accrual adjustments. After a certain level of value of ownership is attained, a positive relations seen, consistent with increased discretionary accrual adjustments associated with stakeholders anticipating managerial entrenchment. Also, it is found that these results are driven by firms with income increasing, as opposed to income decreasing, discretionary accruals.

Practical implications – Shares and options are forming an increasing proportion of executive remuneration that continues to be the subject of much debate amongst regulators and in the media. Showing that the value of share ownership may be an effective internal governance mechanism to help align incentives adds to the debate and has policy implications.

Originality/value – The paper's primary contribution is finding that the value (as opposed to proportion) of share ownership, typically representing a sizeable proportion of managers' undiversified wealth, is a potentially direct driver of theorised incentive alignment and entrenchment effects associated with share ownership.