Southern New Human Resources Strategy Proposal & Professional Reflection Paper Overview: Overall, as you have seen in your course of studies, human resour

Southern New Human Resources Strategy Proposal & Professional Reflection Paper Overview:

Overall, as you have seen in your course of studies, human resources

(HR) is often viewed as a service department for the other departments and is not often enough seen as a partner in decision-making practices. To this end, you will create a strategy proposal that seeks to reposition HR from a simple administrative function to a key strategic role within an organization. Your capstone should showcase your skills and abilities relative to how you plan to be active during the decision-making process and situate yourself as a strategic asset on par with a middle or senior management position. You will also reflect on your journey throughout the Human Resources Management program and how your goals and plans fit within the profession.

Evaluation of Capstone

This capstone will be assessed somewhat differently from other courses you have taken online at SNHU. There are two separate components, but they both operate together to make up the whole capstone experience and are not assessed separately. You will be evaluated on both of them as a unit in determining whether you have demonstrated proficiency in each outcome. Your instructor will guide you through this process, keeping a running narrative of your strengths and weaknesses in relation to the outcomes as you progress through the class. Your work is expected to meet the highest professional standards.

This assessment will address the following outcomes:

Leverage effective customer service and negotiation strategies that build engaging relationships with stakeholders through trust, teamwork, and direct communication

Integrate appropriate talent development and workforce planning strategies to effectively align employee competencies with business goals and provide a measurable return on investment for an organization

Operate as an effective business partner and leader in human resources through clear, concise, and accurate communication skills

Protect the integrity of the business, its employees, and its management practices through appropriate risk management and legal and ethical practices

Recommend appropriate evidence-based strategies that integrate sound, data-driven analysis and critical decision making to support the goals, vision, and mission of the organization

Articulate the importance of a global outlook and cross-cultural approach for human resource professionals in the interest of improving cultural competence and valuing the commonalities, values, and individual uniqueness of organizational members

Advance an organization’s vision and mission through effective leadership strategies that foster collaboration, promote consensus, and guide the organization through adversity and change with resilience and agility

Design, implement, and evaluate strategic human resource programs that deliver customized human resource solutions for organizational challenges and contribute to the success of the business.

Prompt

Develop a human resource strategy proposal that outlines your recommendations for a complete strategic HR overhaul that will advance the global competitiveness of your chosen organization. Be sure to support your proposal with evidence and research you have gathered during your time in this course.

Component One: Human Resources Strategy Proposal

For the first of two capstone components, you will develop a well-organized HR strategy proposal that should lay the foundation for a solid plan to move the HR function from its present state (administrative or technical) to a strong, strategic player within the organization.

You must first choose a company and then describe how you plan to position yourself and your department professionally as a strategic member of the organization. You may choose a real-world company with instructor approval. Keep in mind that the company you choose must be one that already competes at the global level or has the potential to compete in the global arena.

The following sections should be included, but you are not limited to them:

I. Cover Letter: This should be a professionally appropriate business letter addressing the senior management of your company. The letter should briefly introduce the intent of your proposal and detail the various parts that are to come (the proposal itself and how you would implement the proposal, should it be approved). The letter should also use information and evidence supporting your plan that would excite your target audience into reading your proposal.

II. The HR Strategy Proposal: This should include a detailed plan of how you will advance the organization’s vision and mission through effective leadership strategies that foster collaboration, promote consensus, and guide the organization through adversity and change with resilience and agility. Data analysis should be provided to further support your proposal and should also include opposing viewpoints on this issue and explain how your strategy is preferable. Overall, your analysis should highlight how the HR department will operate as an effective business partner and leader.

Your strategy proposal should include, on the whole, a synthesis of the themes and ideas that you have learned during your time in the program. Specifically, your HR proposal should include the following:

o A global outlook and cross-cultural approach for human resource professionals in the interest of improving cultural responsiveness and capitalizing on the commonalities, values, and individual uniqueness of organizational members

o Appropriate evidence-based strategies that integrate sound, data-driven analysis and critical decision making to support the goals, vision, and mission of the organization

o An evaluation of how the department will continue protecting the integrity of the business, its employees, and its management practices through appropriate risk management and legal and ethical practices

o A plan of how to effectively leverage effective customer service and negotiation strategies that build engaging relationships with stakeholders through trust, teamwork, and direct communication

III. Implementation: In this section, you should explain how you would approach employee management at the chosen organization should this proposal be accepted. If the changes you have proposed are accepted include strategies on how to manage talent development and workforce planning, followed by an analysis of a measureable return on investment. You should also include how the role of the human resources department would change with regard to employee negotiations and interactions.

IV. Conclusion: In this final section of the text, you will summarize your proposal and explain how and why your HR strategy proposal is worthy of implementation, while highlighting the practical implications of your proposal for your target audience(s). You should also discuss how you will ensure that your proposal conforms to common business ethical standards.

Guidelines for Submission: Your Component One submission should be 15 to 20 pages in length (in addition to elements such as the title page and reference pages). The document should use double spacing, 12-point Times New Roman font, and one-inch margins. It should follow professional industry standards and include all necessary elements that one would find in a research proposal. It should include a title page, table of contents, professional bibliography, and appendices, if applicable. The information should be cited according to the rules in the Publication Manual of the American Psychological Association, sixth edition. You may include illustrations, photographs, graphs and charts, and other nontextual materials as needed to support the underpinning proposal (though all of the latter should be placed in an appendix or appendices if used).

Component Two: Professional Reflection

For the second and final component of your final project, you will write an essay in which you discuss the process and outcomes of this project, as well as how your coursework culminated in the project. This may include discussions of unforeseen problems or obstacles, and any surprises. The essay should also discuss your identified strengths and problems that you encountered while completing the project. Finally, the essay will examine how the final project will be useful in the job market or in furthering your education.

You should envision this component as a personal reflection on the capstone and your experience in the Human Resource Management program as a whole. For instance, relative to the capstone, you could discuss what you did (or intended to do) and then consider what worked well, what challenges you faced, and what you would change or do differently to make your experience better. In reflecting on your time here at SNHU, you might discuss where you started, where you have ended up, where you see yourself going, and so on. Note that this component is not about evaluating the capstone itself but rather your experience within the capstone project.

Some of the topics that you could address in this final component of this capstone may include the following:

_Overall, what was your capstone experience like?

_Reflect on the significance of the capstone in relation to your own experience at SNHU.

_What connections do you see between your capstone and your academic program?

_How will you apply what you have learned to your future academic and/or professional life?

***15 pages for proposal and 3 pages for Essay***

Will be providing the feedback from the instructor for all three milestones attached. Review and Analysis of Scientific Literature about Diffuse Optical Spectroscopy
1) Find answers to the following questions from the 3 papers included in the assignment file.
2) The diffuse reflectance radial density, R, depends upon a number of variables. Write the variable
symbols here, and define each variable. Include units.
∗
3) Define
, α, ds, and ρs. Include units. What are the average values of these parameters for (a)
normal colon and (b) adenomatous polyp?
4) What is an adenomatous polyp?
∗
5) Why would adenomatous polyps have different
, ds, and ρs than normal colon tissue? Justify
your answer by identifying molecules, organelles, and tissues that could be altered in polyps,
leading to the altered DOS signal.
6) Define every variable in equation 2 of the paper by first-author Stratonnikov.
7) Draw a diagram of a DOS probe contacting human tissue. Draw three photon paths that are
described by equation 2.
8) Equation 19 is the error term for SO2 measurements. Describe 4 conditions under which error in
SO2 measurements is too large for accurate determination of SO2.
9) What is reactive hyperemia?
10) What is/are the physiological signal(s) that trigger(s) hyperemia?
11) What physical change in one tissue structure allows hyperemia to happen? Which tissue
structure?
12) Why could hyperemia be good for the tissue/organ?
13) Why could hyperemia harm the tissue/organ?
Data Analysis for DOS
14) Read the pdf file RaubLab_SO2_CodeValidation…
15) For the remaining 9 individuals’ SO2 measurements, define the following paramters by reading
them from the graphs:
Subject
1
2
3
4
5
6
7
8
9
10
Baseline
SO2 mean
Drop SO2
slope
Minimum
SO2
Maximum
SO2
Hyperemia
%
Hypoxia %
*hyperemia % = maximum SO2/baseline SO2 mean
** hypoxia % = minimum SO2/baseline SO2 mean
16) Subjects 1,6,7,8 were female. Subjects 2,3,4,5,9, and 10 were male. Perform t-tests for each
parameter (6 t-tests in total), to determine if there was a difference between male and female
subject SO2 parameters. Write the t-test results here:
Variable
Female
Male
Effect size
t-statistic
P-value
Significance?
group
group
(difference
(Yes/No)
mean +/mean +/- of means)
SD
SD
Baseline
SO2 mean
Drop SO2
slope
Minimum
SO2
Maximum
SO2
Hyperemia
%
Hypoxia %
17) Comment on the data and likelihood of experimental error. Were there any subjects data that
appeared different than others (outlier)?
18) Outliers in experimental datasets are often caused by uncontrolled or unmeasured variables.
List 5 potential uncontrolled or unmeasured variables in the described experiment that could
have created outliers and significant variation.
SO2 code validation
and quantification
Chris Raub, PhD
Claire Sturek
Ruby Huynh
Jane Lam
3.6.2018
Validation and Method of Quantification
1. We wrote two matlab functions that allow calculation of SO2 and quantification of SO2 parameters from
diffuse reflectance data.
2. To validate the calculation and quantification, we built a diffuse spectroscopy apparatus (consisting of
endoscopy light source, fiberoptic transmission fiber, parallel collection fiber ~ 3 mm away from tranmission
fiber, and a RedTide spectrometer), and collected data from 10 volunteers as part of a class project.
3. DOS data was collected from the pointer fingertip over 180 seconds. The first 60 seconds were at baseline.
Then a pressure cuff from a sphygmomanometer was inflated around the upper arm (~10 seconds). Then, the
pressure was held constant for 30 seconds. Finally, the pressure was released, and return to baseline was
recorded until 180 seconds had elapsed.
4. The 10 SO2 graphs are shown below. Most show a baseline of normoxia, a period of hypoxia, and a return to
baseline normoxia with or without transient hyperemia.
5. Quantification results (region fits and parameters) are shown for Individual 1. Baseline SO2 was 43.8±0.9%.
Maximum hypoxia was 86% of baseline. Maximum hyperemia was 108% of baseline.
6. Conclusions: The magnitude of SO2 values and direction of change with arm cuff pressure and release are
reasonable, lending confidence to both the instrument and code. The code can be applied to analyze SCI
patient data. Caution #1: It is critical to know the time interval of data acquisition. Caution #2: Additional error
could arise from the fact that the SCI data was collected with a different instrument,
SO2 (normalized)
Individual 1
time (seconds)
0.438
0.00894
45
-0.0598
54.3
0.377
2.64
3.73
0.475
0.457
0.00921
76.1
108
86
104
Region best-fit lines
baseline 2
SO2 (normalized)
baselineSO2 mean (normalized)
baselineSO2 standard deviation
(normalized)
baselineSO2 duration (seconds)
dropSO2 slope (%/second)
dropSO2 duration (seconds)
minimum SO2 (normalized)
rising SO2 slope (%/second)
rising SO2 duration (seconds)
maximum SO2 (normalized)
baseline2 SO2 mean (normalized)
baseline2SO2 standard deviation
(normalized)
baseline2SO2 duration (seconds)
hyperemia Percent (%)
hypoxia Percent (%)
change in Baseline (%)
baseline
rise
drop
time (seconds)
SO2 (normalized)
Individual 2
time (seconds)
SO2 (normalized)
Individual 3
time (seconds)
SO2 (normalized)
Individual 4
time (seconds)
SO2 (normalized)
Individual 5
time (seconds)
SO2 (normalized)
Individual 6
time (seconds)
SO2 (normalized)
Individual 7
time (seconds)
SO2 (normalized)
Individual 8
time (seconds)
SO2 (normalized)
Individual 9
time (seconds)
SO2 (normalized)
Individual 10
time (seconds)
Journal of Biomedical Optics 6(4), 457–467 (October 2001)
Evaluation of blood oxygen saturation in vivo
from diffuse reflectance spectra
Alexander A. Stratonnikov
Victor B. Loschenov
General Physics Institute
Laser Biospectroscopy Lab
38, Vavilov Street
Moscow 117942, Russia
Abstract. A simple method to evaluate the hemoglobin oxygen saturation and relative hemoglobin concentration in a tissue from diffuse
reflectance spectra in the visible wavelength range is put forward in
this paper. It was assumed that while oxygenated and deoxygenated
hemoglobin contributions to light attenuation are strongly variable
functions of wavelength, all other contributions to the attenuation including scattering are smooth wavelength functions and can be approximated by Taylor series expansion. Based on this assumption, a
simple, robust algorithm suitable for real time monitoring of the hemoglobin oxygen saturation in the tissue has been derived. This algorithm can be used with different fiber probe configurations for delivering and collecting light passed through the tissue. An experimental
technique using this algorithm has been developed for in vivo monitoring during artery occlusion and in vitro monitoring of blood
samples. The experimental results obtained are presented in the paper. © 2001 Society of Photo-Optical Instrumentation Engineers.
[DOI: 10.1117/1.1411979]
Keywords: tissue spectroscopy; blood oxygenation; tissue absorption; diffuse reflectance.
Paper 90021 received Mar. 31, 1999; revised manuscript received Sep. 26, 2000;
accepted for publication Mar. 19, 2001.
1
Introduction
There are many approaches to evaluate the blood oxygen
saturation in vivo from tissue diffuse reflectance spectra.1–22
Hemoglobin contained in erythrocytes is the main tissue absorber in the visible and very near infrared range. As a hemoglobin absorption spectrum is different for oxygenated and
deoxygenated forms18,23 共by this reason the blood in an artery
and a vein varies in color兲, this fact can be used for quantification of the blood oxygen saturation in the tissue in vivo. The
central problem with the evaluation of blood oxygen saturation for the tissue in vivo is to take into account the influence
of the scattering, other tissue absorbers and heterogeneous
hemoglobin distribution.
To quantify the relative oxyhemoglobin and deoxyhemoglobin concentrations as well as other tissue absorbers in the
tissue using optical spectroscopy, the following two steps are
usually performed. First, the total absorption 共␮ a 兲 and reduced scattering 共␮ ⬘s 兲 tissue coefficients are extracted from
the experimental measurements at several wavelengths. For a
uniform semi-infinite medium it can be done by time resolved
methods in frequency and time domain10,11,20,24,25 or spatially
resolved methods.17,29,26 –30 The number of wavelengths
whereby the total absorption coefficient is evaluated should be
at least equal to the number of the tissue absorbers contributing to absorption in the spectral range under analysis. If the
measurement method gives no way of obtaining absorption
and reduced scattering coefficients independently, for example, in steady-state measurements without spatial resoluAddress all correspondence to Dr. Alexander A. Stratonnikov. Tel/Fax: 095-3246363; E-mail: biospec@online.ru
tion absorption and reduced scattering coefficients are
coupled to each other, some assumption should be done about
behavior of the reduced scattering coefficient or this value
requires independent measurements. Using this information
and applying some model for diffuse reflection dependence
upon tissue optical properties, the absorption coefficient can
be extracted from simple steady-state diffuse reflectance
measurements.31 On evaluating the total tissue absorption coefficient at several wavelengths, the concentrations of individual absorbers may be obtained as it is done in the usual
spectroscopy problem of multicomponent systems. If the absorption spectra of all the species contributing to the tissue
absorption are known, it is done by solving normal equations
with the least square method. The sophisticated chemometrics
methods 共partial least square, principle component analysis19
or singular value decomposition32兲 can be also applied if information about absorbing species is not complete.
An original self-consistent approach for evaluation of the
blood oxygen saturation and the relative hemoglobin concentration from diffuse reflectance spectrum obtained with fiber
probe geometry without spatial resolution is described in this
work. The method is applied in the visible wavelength range,
where the spectral difference between oxygenated and deoxygenated hemoglobin is rather high. The advantage of the proposed approach is its simplicity and applicability to different
fiber probe geometries used to deliver and collect light passed
through the tissue. The relation between a diffuse reflectance
signal and tissue optical properties in terms of photon path
length distribution function is detailed in the next section. The
existing theoretical approaches extracting the absorption coef1083-3668/2001/$15.00 © 2001 SPIE
Journal of Biomedical Optics
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457
Stratonnikov and Loschenov
distribution with some probability function P. The intensity of
a light signal in the receiving fiber or in the integrating sphere
is determined by absorbing and scattering properties of the
tissue as well as by measurement configuration and may be
expressed through the path length probability function by the
following relation:
I/I 0 ⫽
Fig. 1 Integrating sphere geometry for collecting diffuse reflected photons. The sampling depth for this configuration is determined mainly
by the light penetration depth ␦.
ficient are briefly reviewed and discussed therein. Taylor expansion method is presented in Sec. 3. In linear approximation it results in an effective algorithm for blood oxygen
saturation calculation. An experimental setup for diffuse reflectance and diffuse transmittance measurements is described
in Sec. 4. Finally, the experimental results obtained on human
skin during artery occlusion and blood samples during photochemical deoxygenation are presented and discussed in
Sec. 5.
2 Diffuse Reflectance and Photon Path Length
Distribution Function
To evaluate the spectral dependencies of absorption and scattering coefficients it is convenient to consider the light attenuation A共␭兲 defined by the following expression:
A 共 ␭ 兲 ⫽⫺ln
冉冊
I
,
I0
共1兲
where I 0 and I are the total photon flows coming out from the
delivery fiber and entering into the receiving fiber correspondingly. In the case of integrating sphere configuration the value
I is the integrated photon flow measured by the sphere 共see
Figures 1 and 2兲. Sometimes the dependence 共1兲 is called the
absorption without correction for the scattering.
Due to the strong tissue scattering the photon path lengths
through the tissue contributing the measured signal have a
Fig. 2 Probe arrangement with distantly placed fibers for the measurement of tissue diffuse reflectance spectra in vivo. The sampling depth
is determined by the light penetration depth ␦ and fiber separation
distance d.
458
Journal of Biomedical Optics
䊉
October 2001
䊉
冕
⬁
0
P 共 ␮ s ,g,l 兲 •exp共 ⫺ ␮ a l 兲 dl,
共2兲
where ␮ s is the scattering tissue coefficient, ␮ a is the absorption coefficient, g is the scattering anisotropy factor, l is the
photon path length through the tissue on the trajectory between the delivering and receiving fibers 共see Figure 2兲, and
the dimensionless value P ( ␮ s ,g,l ) dl is the probability that
the photon path length will be in the interval 关 l,l⫹dl 兴 between the delivering and receiving fibers in the absence of
absorption 共path length distribution function兲. The path length
distribution function P depends on the scattering tissue properties 共␮ s and g兲 as well as on the geometry of the measurements 共fiber probe spatial configuration兲. The dimension of P
function is the inverse dimension of the length. The integral of
the distribution function over all photon path lengths 共normalization of the path length distribution function兲 determines the
attenuation of photon flux between the delivery and receiving
fibers due to the scattering alone. It should be also noted here
that integral 共2兲 represents Laplace transform of the path
length distribution function P(l兲.
As mentioned above, the path length distribution function
is strongly dependent on the spatial configuration of the fiber
probe as its geometry defines the trajectories of photons,
which passed through the tissue and reached the detector. Two
limiting cases of geometrical configurations for the semiinfinite medium are usually discussed. The first is the integrating sphere arrangement when all light reemitted from the tissue is collected as shown in Figure 1. Practically it may be
realized only with the use of an integrating sphere for collecting all the diffuse reflected light. However, the use of the
integrating sphere is very inconvenient for in vivo measurements. A sampling depth for this configuration is determined
mainly by the light penetration depth ␦. In the second limiting
case the delivery and receiving fibers 共or a light emitter and a
detector兲 are placed apart at the distance d which is much
greater than the fiber diameter 共size of the emitter and the
detector兲 as shown in Figure 2. In this case the photon trajectories through the tissue form a banana shaped region with the
ends at the positions of the delivery and receiving fibers. The
sampling depth for this configuration is proportional to 冑2d/4
in the weak absorption limit 共dⰆ␦兲 and 冑d ␦ /2 in the strong
absorption limit 共 d Ⰷ␦ 兲.33,34 Thus, in this case increasing the
fiber separation makes it possible to increase the sampling
depth. This configuration is applied to cerebral blood oxygen
saturation measurements in the near infrared spectral range.
Of course, there may be intermediate cases such as closely
spaced delivery and receiving fibers which are greater in diameter than the distance between the fibers. Approximate analytical solutions relating tissue optical properties and diffuse
reflected signal intensity have been obtained only for these
limiting cases of the integrating sphere and the spatially
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Evaluation of Blood Oxygen Saturation . . .
placed fibers. For intermediate cases one may use a collection
efficiency factor scaling the measured signal to these analytical expressions.
In the case of a transparent medium for a configuration
when delivering and receiving fibers are placed on opposite
sides of a sample with thickness L, all the photons have the
same path length L, and the path length distribution function
is reduced to Dirac delta function: P ( l ) ⫽ ␦ ( l⫺L ) . On substituting this function in Eq. 共2兲 it is reduced to the Beer–
Lambert law relating signal attenuation in the nonscattering
absorbing medium with the absorption coefficient ␮ a and the
path length L
A⫽⫺ln
冉冕
⬁
0
冊
␦ 共 l⫺L 兲 •exp共 ⫺ ␮ a l 兲 dl ⫽ ␮ a •L.
共3兲
In the presence of the scattering the relation between the
measured signal attenuation and the absorption coefficient is
complicated. Accurate approaches for obtaining the absorption and scattering tissue coefficients are based on the time
resolved measurements. The time resolved reemittance signal
represents in fact the path length distribution function with
change of product speed of light in the tissue and time on path
length l multiplied by the absorption term exp(-␮al). An analytical approximation for the path length distribution function
共with zero boundary condition兲 for the fiber configuration
shown in Figure 2 has been obtained from the diffusion
theory24
P 共 l 兲 •exp共 ⫺ ␮ a l 兲 ⫽z 0 共 4 ␲ D 兲 ⫺3/2l ⫺5/2
冉
⫻exp ⫺
d 2 ⫹z 20
4Dl
冊
•exp共 ⫺ ␮ a l 兲 •ds,
共4兲
where z 0 ⫽1/␮ ⬘s , ␮ s⬘ ⫽ ␮ s ( 1⫺g ) ,D⫽1/3␮ ⬘s , d is distance between the source and the detector, ds is the cross-sectional
area of the receiving fiber. Fitting the experimental time resolved reemitted signal with function 共4兲 共or more sophisticated one taking into account different boundary
conditions25,35兲 one can get the values of ␮ a and ␮ ⬘s . 24 But
this method requires a complicated technique for its realization and makes application in clinical conditions difficult.
The steady-state experimental methods are easier to apply
in practice. In diffuse approximation the formula relating the
intensity of the steady-state measured signal with tissue optical properties and the fiber separation distance can be obtained directly from Eq. 共2兲. Substituting relation 共4兲 for the
path length distribution function into Eq. 共2兲 and calculating
the resulting integral we obtain the following relation for the
steady-state case in the diffusion approximation:
I/I 0 ⫽
⫽
冕
⬁
0
2 ␲ ␮ s⬘
•
冉 冊
1
␦
⫹
1 1
• •exp共 ⫺d/ ␦ 兲 •ds,
d d2
␦ ⫽1/冑3 ␮ a 共 ␮ a ⫹ ␮ s⬘ 兲 ⬇1/冑3 ␮ a ␮ s⬘ .
R d ⫽I/I 0 ⫽exp共 ⫺A 兲 ⫽1⫺
K
S
冉冑
冊
S
1⫹2 ⫺1 ,
K
共5兲
共6兲
where K and S are absorption and scattering Kubelka–Munk
coefficients, respectively. The Kubelka–Munk absorption coefficient K can be related to the tissue absorption coefficient
␮ a . In Ref. 9 this approach was used to evaluate the blood
oxygen saturation by modeling tissue absorption as a sum of
oxygenated and deoxygenated hemoglobin and approximating
the Kubelka–Munk scattering coefficient by a smooth wavelength function. Actually, this approach is very close to ours
given bellow. The difference is that we are not restricted to the
particular fiber probe geometry and derive the results starting
from the exact relation 共2兲 for the diffuse reflectance 共or transmittance�…
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