Value congruence and job-related attitudes in a nonprofit organization: A competing values approach

Researchers have highlighted the importance of the nonprofit sector, its continued growth, and a relative lack of literature particularly related to nonprofit organizational values. Therefore, this study investigates organizational culture in a human services nonprofit organization. The relationship between person-organization value congruence and employee and volunteer job-related attitudes is examined (N = 227). Following initial qualitative enquiry, confirmatory factor analyses of the Competing Values Framework and additional values revealed five dimensions of organizational values. The relationship between value congruence, and employee and volunteers' job-related attitudes was examined using polynomial regression techniques. Analyses revealed that for employees, job-related attitudes were influenced strongly by organization values ratings, particularly when exceeding person ratings of the same values. For volunteers, person value ratings exceeding organization value ratings were especially detrimental to their job-related attitudes. Findings are discussed in terms of their theoretical and practical implications.

Non-linear and linear postulations of technology adoption determinants

Using polynomial regression and response surface analysis to examine the non-linearity between variables, this study demonstrates that better analytical nuances are required to investigate the relationships between constructs when the underlying theories suggest non-linearity. By utilising the Theory of Planned Behaviour (TPB), Ettlie’s adoption stages as well as employing data gathered from 162 owners of Small and Medium-sized Enterprises (SMEs), our findings reveal that subjective norms and attitude have differing influences upon behavioural intention in both the evaluation and trial stages of the adoption.

Robust and High-resolution Voiced/Unvoiced Classification in Noisy Speech Using A Signal Smoothness Criterion

We propose a novel technique for robust voiced/unvoiced segment detection in noisy speech, based on local polynomial regression. The local polynomial model is well-suited for voiced segments in speech. The unvoiced segments are noise-like and do not exhibit any smooth structure. This property of smoothness is used for devising a new metric called the variance ratio metric, which, after thresholding, indicates the voiced/unvoiced boundaries with 75% accuracy for 0dB global signal-to-noise ratio (SNR). A novelty of our algorithm is that it processes the signal continuously, sample-by-sample rather than frame-by-frame. Simulation results on TIMIT speech database (downsampled to 8kHz) for various SNRs are presented to illustrate the performance of the new algorithm. Results indicate that the algorithm is robust even in high noise levels.

On the Average Case Communication Complexity for Detection in Sensor Networks

The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space viewpoint is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces $\mathcal{S_I}$ and $\mathcal{S_C}$ and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating $\mathcal{S_I}$ and $\mathcal{S_C}$ is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. The average case CC of the relevant greater-than (GT) function is characterized within two bits. In the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm.

Distributed intrusion detection in the presence of correlated sensor readings: Signal-space and communication-complexity view-point

The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space view-point is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces f(s) and f(g) and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating f(s) and f(g) is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication-complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. Extensions to the multi-party case is straightforward and is briefly discussed. The average case CC of the relevant greaterthan (CT) function is characterized within two bits. Under the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm. 2010 Elsevier B.V. All rights reserved.

Spectral-envelope-group-delay models for transients

Transient signals such as plosives in speech or Castanets in audio do not have a specific modulation or periodic structure in time domain. However, in the spectral domain they exhibit a prominent modulation structure, which is a direct consequence of their narrow time localization. Based on this observation, a spectral-domain AM-FM model for transients is proposed. The spectral AM-FM model is built starting from real spectral zero-crossings. The AM and FM correspond to the spectral envelope (SE) and group delay (GD), respectively. Taking into account the modulation structure and spectral continuity, a local polynomial regression technique is proposed to estimate the GD function from the real spectral zeros. The SE is estimated based on the phase function computed from the estimated GD. Since the GD estimation is parametric, the degree of smoothness can be controlled directly. Simulation results based on synthetic transient signals generated using a beta density function are presented to analyze the noise-robustness of the SEGD model. Three specific applications are considered: (1) SEGD based modeling of Castanet sounds; (2) appropriateness of the model for transient compression; and (3) determining glottal closure instants in speech using a short-time SEGD model of the linear prediction residue.

Event-triggered sampling using signal extrema for instantaneous amplitude and instantaneous frequency estimation

Event-triggered sampling (ETS) is a new approach towards efficient signal analysis. The goal of ETS need not be only signal reconstruction, but also direct estimation of desired information in the signal by skillful design of event. We show a promise of ETS approach towards better analysis of oscillatory non-stationary signals modeled by a time-varying sinusoid, when compared to existing uniform Nyquist-rate sampling based signal processing. We examine samples drawn using ETS, with events as zero-crossing (ZC), level-crossing (LC), and extrema, for additive in-band noise and jitter in detection instant. We find that extrema samples are robust, and also facilitate instantaneous amplitude (IA), and instantaneous frequency (IF) estimation in a time-varying sinusoid. The estimation is proposed solely using extrema samples, and a local polynomial regression based least-squares fitting approach. The proposed approach shows improvement, for noisy signals, over widely used analytic signal, energy separation, and ZC based approaches (which are based on uniform Nyquist-rate sampling based data-acquisition and processing). Further, extrema based ETS in general gives a sub-sampled representation (relative to Nyquistrate) of a time-varying sinusoid. For the same data-set size captured with extrema based ETS, and uniform sampling, the former gives much better IA and IF estimation. (C) 2015 Elsevier B.V. All rights reserved.

Dietary carbohydrate requirement of Heterobranchus longifilis

The dietary carbohydrate requirement of Heterobranchus longifilis was evaluated in two separate experiments.In the first experiment, varying levels of carbohydrate ranging from 28, 24 to58 72% were fed to the fish of mean weight 1.83~c0.02g. Results revealed that the polynomial regression curve for the mean weight gain and the carbohydrate levels did not present a point where Y-max is equal to X-max and so the requirement was not obtained. The second experiment was therefore, conducted with lower levels of carbohydrate ranging from 17.00 to 20.86% and fed to fish with mean weight 0.49~c0.02g. Based on growth and feed efficiency data the carbohydrate requirement was determined to be 19.5%

Partial and total replacement of fishmeal with poultry by-product meal in diets for gibel carp, Carassius auratus gibelio Bloch

Triplicate groups of gibel carp Carassius auratus gibelio Bloch (initial body weight: 4.89 g) were fed for 8 weeks at 24.8-30.8 degrees C with nine isonitrogenous and isoenergetic diets. The control diet (F1) used white fishmeal (FM) as the sole protein source. In the other eight diets (F2-F9), 40.5-100% of FM protein was substituted by poultry by-product meal (PBM) at 8.5% increments. The specific growth rate (SGR), feed efficiency ratio, protein efficiency ratio, protein retention efficiency and energy retention rate for fish fed PBM diets (F2-F9) were all higher, but not always significantly, than those for fish fed F1. All apparent digestibility coefficients for fish fed PBM diets were lower than those for fish fed F1. Fish fed F1 had a significantly higher hepatosomatic index value than fish fed PBM diets (P < 0.05). No significant (P > 0.05) effect of diet was found in whole-body moisture and fat content. Whole-body protein and energy content for fish fed PBM diets were slightly higher than that for fish fed F1. The optimal replacement level of FM by PBM was estimated by second-order polynomial regression to be 66.5% in protein.

Factorial Design of Cement Slurries Containing Limestone Powder for Self-Consolidating Slurry-Infiltrated Fiber Concrete

Slurries with high penetrability for production of Self-consolidating Slurry Infiltrated Fiber Concrete (SIFCON) were investigated in this study. Factorial experimental design was adopted in this investigation to assess the combined effects of five independent variables on mini-slump test, plate cohesion meter, induced bleeding test, J-fiber penetration test and compressive strength at 7 and 28 days. The independent variables investigated were the proportions of limestone powder (LSP) and sand, the dosages of superplasticiser (SP) and viscosity agent (VA), and water-to-binder ratio (w/b). A two-level fractional factorial statistical method was used to model the influence of key parameters on properties affecting the behaviour of fresh cement slurry and compressive strength. The models are valid for mixes with 10 to 50% LSP as replacement of cement, 0.02 to 0.06% VA by mass of cement, 0.6 to 1.2% SP and 50 to 150% sand (% mass of binder) and 0.42 to 0.48 w/b. The influences of LSP, SP, VA, sand and W/B were characterised and analysed using polynomial regression which identifies the primary factors and their interactions on the measured properties. Mathematical polynomials were developed for mini-slump, plate cohesion meter, J-fiber penetration test, induced bleeding and compressive strength as functions of LSP, SP, VA, sand and w/b. The estimated results of mini-slump, induced bleeding test and compressive strength from the derived models are compared with results obtained from previously proposed models that were developed for cement paste. The proposed response models of the self-consolidating SIFCON offer useful information regarding the mix optimization to secure a highly penetration of slurry with low compressive strength

Influence of mix proprtions on rheolgy of cement grouts containing limestone powder

In this paper the parameters of cement grout affecting rheological behaviour and compressive strength are investigated. Factorial experimental design was adopted in this investigation to assess the combined effects of the following factors on fluidity, rheological properties, induced bleeding and compressive strength: water/binder ratio (W/B), dosage of superplasticiser (SP), dosage of viscosity agent (VA), and proportion of limestone powder as replacement of cement (LSP). Mini-slump test, Marsh cone, Lombardi plate cohesion meter, induced bleeding test, coaxial rotating cylinder viscometer were used to evaluate the rheology of the cement grout and the compressive strengths at 7 and 28 days were measured. A two-level fractional factorial statistical model was used to model the influence of key parameters on properties affecting the fluidity, the rheology and compressive strength. The models are valid for mixes with 0.35-0.42 W/B, 0.3-1.2% SP, 0.02-0.7% VA (percentage of binder) and 12-45% LSP as replacement of cement. The influences of W/B, SP, VA and LSP were characterised and analysed using polynomial regression which can identify the primary factors and their interactions on the measured properties. Mathematical polynomials were developed for mini-slump, plate cohesion meter, inducing bleeding, yield value, plastic viscosity and compressive strength as function of W/B, SP, VA and proportion of LSP. The statistical approach used highlighted the limestone powder effect and the dosage of SP and VA on the various rheological characteristics of cement grout

State-space model identification of a wireless THz network

We model the large scale fading of wireless THz communications links deployed in a metropolitan area taking into account reception through direct line of sight, ground or wall reflection and diffraction. The movement of the receiver in the three dimensions is modelled by an autonomous dynamic linear system in state-space whereas the geometric relations involved in the attenuation and multi-path propagation of the electric field are described by a static non-linear mapping. A subspace algorithm in conjunction with polynomial regression is used to identify a Wiener model from time-domain measurements of the field intensity.

Wiener-System subspace identification for mobile wireless mm-wave networks

We discuss the feasibility of wireless terahertz communications links deployed in a metropolitan area and model the large-scale fading of such channels. The model takes into account reception through direct line of sight, ground and wall reflection, as well as diffraction around a corner. The movement of the receiver is modeled by an autonomous dynamic linear system in state space, whereas the geometric relations involved in the attenuation and multipath propagation of the electric field are described by a static nonlinear mapping. A subspace algorithm in conjunction with polynomial regression is used to identify a single-output Wiener model from time-domain measurements of the field intensity when the receiver motion is simulated using a constant angular speed and an exponentially decaying radius. The identification procedure is validated by using the model to perform q-step ahead predictions. The sensitivity of the algorithm to small-scale fading, detector noise, and atmospheric changes are discussed. The performance of the algorithm is tested in the diffraction zone assuming a range of emitter frequencies (2, 38, 60, 100, 140, and 400 GHz). Extensions of the simulation results to situations where a more complicated trajectory describes the motion of the receiver are also implemented, providing information on the performance of the algorithm under a worst case scenario. Finally, a sensitivity analysis to model parameters for the identified Wiener system is proposed.

MIMO Wiener model identification for large scale fading of wireless mobile communications links

The large scale fading of wireless mobile communications links is modelled assuming the mobile receiver motion is described by a dynamic linear system in state-space. The geometric relations involved in the attenuation and multi-path propagation of the electric field are described by a static non-linear mapping. A Wiener system subspace identification algorithm in conjunction with polynomial regression is used to identify a model from time-domain estimates of the field intensity assuming a multitude of emitters and an antenna array at the receiver end.

Effects of dietary urea levels on milk protein fractions of Holstein cows

The aim of this study was to evaluate the effects of substituting soybean meal for urea on milk protein fractions (casein, whey protein and non-protein nitrogen) of dairy cows in three dietary levels. Nine mid-lactation Holstein cows were used in a 3 x 3 Latin square arrangement, composed of 3 treatments, 3 periods of 21 days each, and 3 squares. The treatments consisted of three different diets fed to lactating cows, which were randomly assigned to three groups of three animals: (A) no urea inclusion, providing 100% of crude protein (CP), rumen undegradable protein (RUP) and rumen degradable protein (RDP) requirements, using soybean meal and sugarcane as roughage; (B) urea inclusion at 7.5 g/kg DM in partial substitution of soybean meal CP equivalent; (C) urea inclusion at 15 g/kg DM in partial substitution of soybean meal CP equivalent. Rations were isoenergetic and isonitrogenous-1 60 g/kg DM of crude protein and 6.40 MJ/kg DM of net energy for lactation. When the data were analyzed by simple polynomial regression, no differences were observed among treatments in relation to milk CP content, true protein, casein, whey protein, non-casein and non-protein nitrogen, or urea. The milk true protein:crude protein and casein:true protein ratios were not influenced by substituting soybean meal for urea in the diet. Based on the results it can be concluded that the addition of urea up to 15 g/kg of diet dry matter in substitution of soybean meal did not alter milk protein concentration casein, whey protein and its non-protein fractions, when fed to lactating dairy cows. (c) 2007 Elsevier B.V. All rights reserved.