Read the Pachankis article on affirmative therapy. Review the APA guidelines for working with lesbian, gay, bisexual, transgender, and questioning (LGBTQ) clients in counseling. Then, review the VFE® course media Affirmative Therapy. Take detailed notes on the competencies outlined in the APA guidelines.
The Assignment:
In a 3- to 4-page paper, write a summary of the VFE® session, noting the competencies and practices that were effectively demonstrated by the counselor. Use the Learning Resources, APA guidelines, and the Pachankis article on affirmative therapy to support your summation. Include the following:
⢠Explain how the counselor effectively applied at least three competencies outlined in the APA guidelines and the article. Provide examples.
⢠With regard to each competency you selected, share insights that you gained about the application of this competency from the dialogue between the two counselors (in other words, that you did not gain from observation of the session alone).
⢠Explain how the counselor demonstrated effective cultural competency, providing examples to support your response.
⢠Based on your current level of knowledge and skill, suggest one recommendation you might make to the counselor to improve his or her effectiveness.
Sample Solution
an analytical technique is utilized in [9] to define the superior size and vicinity of dg unit to reduce only the strength loss. willis in [10] presented the guideline called 2/three rule for most excellent dg placement for loss reduction. the most appropriate dg length with uniformly disbursed load become 2/three of the overall load and the most useful location was 2/3 of the total distance. in (1) used evolutionary programming method for most beneficial placement and size of dg in radial distribution feeder. in (2) and (3), they defined a diverse objective characteristic to find greatest sitting and sizing of dg. the improvement of voltage and loss minimization is used as goal feature in (4). the proposed techniques based on multiobjectives for most beneficial vicinity of dg gadgets in radial distribution. ref (five) studied the results of the good sized parameter along with reliability, loss reduction and performance to optimize losses and improve voltage profile. genetic algorism is method that utilized in (6) to discover choicest placement and length of chp and pv generation so that you can minimize the energy losses. in (7), a unique optimization technique implemented an artificial bee colony (abc) algorithm to locate the surest dg length, electricity component and location to reduce the whole strength loss. particle swarm optimization (pso) algorithm is applied to determine the placement and sizing of distributed generation in (10). minimizing overall price gadget and minimizing energy losses is considered as goal capabilities. the effect of sitting and sizing dg on energy gadget network contemplated on improving voltage profile, minimizing electricity losses and increasing electricity transfer capability. reference (11) showed the assessment between pso and genetic algorithm (ga) in fixing dg allocation. the end result indicated the perfection of pso in comparison to ga in phrases of solution first-rate and variety of iteration optimization methods. furthermore in (12), supplied mixed techniques with ga as well as pso. multiobjectives optimization hassle was formulated to achieve the optimum size and place for dg in distribution gadget. the proposed objectives were to decrease the electricity losses, maximize the voltage stability and improve voltage regulation in radial distribution. ga changed into used for sitting of dg whilst pso is solved for sizing of dg. biogeography primarily based optimization (bbo) is provided to define the place and size of dg and capacitors in (15). reducing energetic and reactive losses is an goal characteristic deliberating the fee discount of losses at one-of-a-kind load degrees. in reference (16), a hybrid set of rules pso & hbmo is used for premiere placement and sizing>
an analytical technique is utilized in [9] to define the superior size and vicinity of dg unit to reduce only the strength loss. willis in [10] presented the guideline called 2/three rule for most excellent dg placement for loss reduction. the most appropriate dg length with uniformly disbursed load become 2/three of the overall load and the most useful location was 2/3 of the total distance. in (1) used evolutionary programming method for most beneficial placement and size of dg in radial distribution feeder. in (2) and (3), they defined a diverse objective characteristic to find greatest sitting and sizing of dg. the improvement of voltage and loss minimization is used as goal feature in (4). the proposed techniques based on multiobjectives for most beneficial vicinity of dg gadgets in radial distribution. ref (five) studied the results of the good sized parameter along with reliability, loss reduction and performance to optimize losses and improve voltage profile. genetic algorism is method that utilized in (6) to discover choicest placement and length of chp and pv generation so that you can minimize the energy losses. in (7), a unique optimization technique implemented an artificial bee colony (abc) algorithm to locate the surest dg length, electricity component and location to reduce the whole strength loss. particle swarm optimization (pso) algorithm is applied to determine the placement and sizing of distributed generation in (10). minimizing overall price gadget and minimizing energy losses is considered as goal capabilities. the effect of sitting and sizing dg on energy gadget network contemplated on improving voltage profile, minimizing electricity losses and increasing electricity transfer capability. reference (11) showed the assessment between pso and genetic algorithm (ga) in fixing dg allocation. the end result indicated the perfection of pso in comparison to ga in phrases of solution first-rate and variety of iteration optimization methods. furthermore in (12), supplied mixed techniques with ga as well as pso. multiobjectives optimization hassle was formulated to achieve the optimum size and place for dg in distribution gadget. the proposed objectives were to decrease the electricity losses, maximize the voltage stability and improve voltage regulation in radial distribution. ga changed into used for sitting of dg whilst pso is solved for sizing of dg. biogeography primarily based optimization (bbo) is provided to define the place and size of dg and capacitors in (15). reducing energetic and reactive losses is an goal characteristic deliberating the fee discount of losses at one-of-a-kind load degrees. in reference (16), a hybrid set of rules pso & hbmo is used for premiere placement and sizing>
