Using the Life Profile Feature on KPAstrology.AI

Interpreting the Life Profile Chart on KPAstrology.AI.

.Welcome to the Life Profile feature!

This is a compelling feature in the KPAstro toolkit. However, at first glance, it may seem overly complex for many. Once you understand it, it is neither complex nor difficult to use. We will cover two topics below: a) What the chart means, what the various colors represent, and b) How to interpret the chart about your individual life.

So let’s begin…

What does the chart show?

On the left is a sample clip of the chart. Simply stated, each bar represents a day in your life. The subparts inside each such bar are colored to represent the 12 houses in the birth chart. Remember, each house in a birth chart represents an aspect of our life.

For example, the first house is about Self, the second House is about financial assets, finances, family, childhood home, nutrition, and voice, the third house is about siblings, marketing and media, contracts, short-distance travel (commute), and the fourth house is about motherhood, real estate, properties, vehicles, home interiors, and so on.

Combine these ideas.

The chart shows what aspects of your life will dominate that day. This picture represents two perspectives.

a) The aspects of your life, the cosmic energies supporting that day

b) The aspects of your life that will be highlighted or at the top of your mind that day.

Hence, you use this chart weekly to align with those energies and maximize your life.

Logically, we all want to fly with the wind behind us, helping us. No one wants to fly with strong headwinds slowing us down. It’s precisely that principle. Align your actions on any day to the areas the cosmos supports. Over time, this will make life appear much more seamless than you have ever experienced.

Back to the chart… each bar represents an entire day in your life. So, one look at the bar and it tells the aspects of your life that you should spend your energy on that day. Should you be writing poetry or creating a piece of art or working on your finances, or dedicating yourself to study or relationships…? The chart will tell you what the cosmos is supporting you in.

Let’s look at the same profile chart for a more extended period, say, 4 years.

This is a life profile chart for 4 years (see the dates on the bottom of the chart). It is the same concept, 12 houses, 12 colors, but for 4 years, not just a day or week. Each bar in this chart is exactly as before – one day. Because there are so many days in 4 years, it gets compressed into this chart and appears like modern art!

Art, it is. Your life.

It’s a wonderfully orchestrated choreography. Learn to dance with it, life will be a joyful experience. If you remain misaligned, it will feel like a burden.

One glance at the chart on the right can show when there are significant changes in your life. See the red ellipse on the chart. What do you see? An important shift in this individual’s life. What is that change? Observe carefully. The first house (on the bottom) (grey) is absent – meaning the self is not present or weak. The 2nd house of finances, family, and nutrition has grown, meaning it will take most of your attention; the 3rd house of siblings is not visible; the 4th house of home, mother, and motherhood is strong; 5th of creativity and children is substantial, 6th house of work, service, humility, minor health issues has risen, the 7th house of spousal relationships, and other relationships is absent, 8th house of sudden changes, windfalls, unearned income, deep study, the study of esoteric subjects, research, worries, karmic paybacks is joining the 6th house and has also grown. The 9th, 10th, 11th, and 12th houses are all absent, meaning the houses discussed above will dominate the individual’s minds on that day – to the exclusion of everything else.

See this chart – it is for an even longer period. 10 years. See the shifts that occur around Jan 2024 (marked in red for your reference). The 1st house representing self, becomes dominant and strong. 10th house of career (yellow and marked by a red ellipse) begins to shrink and become sparse (as compared to the previous years where the yellow is brighter, and much larger in area).

To summarize…

A quick look at this chart will tell us when it would be a good time in those four years to begin an education program, purchase property, look for a job, travel, sign contracts, expect expenses, expect cash flows or windfall, build our social circles, or spend time with ourselves.

This is the power of the Life Profile feature and its chart.

Currently, you can visualize 3 months at any time. We have limited it to 3 months for technical reasons. You can change the start date and visualize any three months of your life. However, that will soon be available to handle any time you desire.

We will soon release another video on this topic. We hope that the above description helps get you started. Remember, the more you do it, the easier it gets.

CP

Aviation Human Factors Pioneer

Stanley Roscoe (1920-2007)

Through my Masters degree, most of my papers focused on Aviation Human Factors. Each time I looked into literature, Stan Roscoe’s work couldn’t be missed.

Stanley Roscoe was a prominent figure in aviation human factors, best known for his contributions to enhancing aviation safety. Roscoe’s work focused on understanding how human performance and behavior impact aviation operations, with the ultimate goal of minimizing errors and improving overall safety. His book on flightdeck performance (O’Hare & Roscoe, 1990) provides a unique perspective on human interactions with the machine. 

Roscoe’s research often delves into the cognitive and psychological aspects of human performance in aviation, examining factors like decision-making, communication, and workload management. He emphasized the importance of designing aviation systems considering human capabilities and limitations and creating training programs that enhance pilot and crew performance. Roscoe’s work not only advanced our theoretical understanding of human factors in aviation but has also influenced practical applications, leading to the development of training protocols and safety measures that have contributed to the continual improvement of aviation safety standards worldwide. 

I was particularly interested in his work on developing a metric known as the Transfer Effectiveness Ration (TER) (Roscoe, 1971). 

No work in aviation human factors will be complete without a thorough study of some (or all) of Roscoe’s work. 

CP

References: 

O’Hare, D., & Roscoe, S. N. (1990). Flightdeck performance: The human factor.

Roscoe, S. N. (1971). Incremental transfer effectiveness. Human Factors13(6), 561-567.

The Swiss Ephemeris

The Swiss Ephemeris is a high-precision ephemeris developed by Astrodienst AG, a Swiss company specializing in astrology software and services. It provides accurate astronomical data such as positions of celestial bodies (e.g., planets, asteroids, and stars) at specific times and locations. Decoding the Swiss Ephemeris involves understanding its data format and using appropriate software or programming libraries to extract and interpret the desired information. Here’s a general overview of how you might decode the Swiss Ephemeris:

1. **Understand the Ephemeris Data Format**: The Swiss Ephemeris data is typically provided in binary or ASCII format. Each record in the ephemeris file represents the positions of celestial bodies at a specific date and time.
2. **Choose a Programming Language or Software**: Decide on the programming language or software environment you’ll use to decode the Swiss Ephemeris. Popular choices include Python, C/C++, and specialized astrology software such as Astrolog or Kepler.
3. **Use Swiss Ephemeris Libraries or APIs**: Astrodienst provides Swiss Ephemeris libraries and APIs for various programming languages, including C, C++, Java, and .NET. These libraries simplify the process of accessing and decoding ephemeris data. You can download the appropriate library for your chosen language from the Astrodienst website.
4. **Open and Read Ephemeris Files**: If you’re working with binary ephemeris files, you’ll need to open them using file I/O functions provided by your programming language. For ASCII files, you can read them line by line and parse the data accordingly.
5. **Extract Desired Ephemeris Data**: Once you’ve opened the ephemeris file, extract the relevant data fields such as the positions of planets or other celestial bodies. Each record in the ephemeris file will contain information about the positions of multiple bodies at a specific date and time.
6. **Convert Coordinates if Necessary**: Depending on your application, you may need to convert the celestial coordinates provided by the Swiss Ephemeris into a different coordinate system or reference frame.
7. **Interpret the Data**: Finally, interpret the decoded ephemeris data according to your requirements. For example, you might use the positions of planets to generate astrological charts or perform astronomical calculations.

Here’s a simplified example in Python using the Swiss Ephemeris Python library (`swisseph`):

“`python

import swisseph as swe
Code Sample:
# Set path to ephemeris file
swe.set_ephe_path(‘/path/to/ephemeris/files’)
# Specify the date and time
year, month, day, hour = 2024, 2, 7, 12
# Initialize Swiss Ephemeris
swe.set_sid_mode(swe.SIDM_LAHIRI)
swe.set_topo(0, 0, 0) # Latitude, longitude, and altitude (here, set to 0)
# Calculate planetary positions
planet_positions = swe.calc_ut(year, month, day, hour, swe.SUN) # Example for the Sun
# Extract relevant information
longitude = planet_positions[0][0] # Longitude
latitude = planet_positions[0][1] # Latitude
print(“Sun’s position (longitude, latitude):”, longitude, latitude)
“`

This example demonstrates how to use the `swisseph` library to calculate the position of the Sun using the Swiss Ephemeris. Make sure to adjust the path to the ephemeris files (`set_ephe_path`) and specify the desired celestial body and date/time parameters accordingly.

CP Jois

Aviation Moment

Chicago’s O’Hare Airport. An ANA 777 waits at Gate 16A for departure for its long haul to Tokyo’s Narita airport.

The beauty of aviation never ceases to amaze.

Navigation

History of Flight Management Computers

Flight Management Computers (FMCs) have played a crucial role in revolutionizing aviation by automating navigation, reducing pilot workload, and enhancing flight efficiency. The evolution of FMCs is a story of innovation, integration, and the seamless fusion of computer technology with aviation.

The concept of automated flight management dates back to the 1950s, when the airline industry recognized the need for improved navigation and flight planning systems. Early systems were rudimentary, relying on analog computers and basic navigation aids.

In the 1970s, the advent of digital technology paved the way for more advanced FMCs. These systems began to appear in larger commercial aircraft, offering functionalities such as route optimization, altitude and speed control, and fuel management. The Boeing 767, introduced in 1982, was one of the first aircraft to incorporate a fully integrated FMC.

By the 1980s and 1990s, FMCs had become standard in many modern aircraft, providing pilots with the ability to program routes, calculate fuel requirements, manage the autopilot, and handle various flight phases. These computers relied on databases of waypoints, airways, and airports, enabling precise navigation even in complex airspaces.

The turn of the century brought about even more sophisticated FMCs. Integrated with advanced satellite-based navigation systems like GPS, FMCs could accurately determine an aircraft’s position in real-time, allowing for precise navigation along curved paths and optimized routes. This marked a significant leap in efficiency and safety.

In recent years, FMCs have evolved to address modern challenges such as fuel efficiency and environmental impact. Airlines and aircraft manufacturers are increasingly focusing on developing FMC software that considers factors like wind patterns, engine performance, and cost-effective routing to minimize fuel consumption and emissions.

Looking ahead, the integration of artificial intelligence, machine learning, and advanced data analytics is likely to shape the next phase of FMC evolution. These technologies could enable FMCs to predict and adapt to weather conditions, optimize routes dynamically, and further reduce human intervention while ensuring safety remains paramount.

Moreover, the rise of digital connectivity has enabled the transfer of real-time data between the aircraft and ground systems, facilitating better decision-making and operational efficiency. Today’s FMCs are more intuitive, user-friendly, and capable of adapting to changing conditions, enhancing the pilot’s ability to manage the flight effectively.

In summary, the history of Flight Management Computers is a testament to the ongoing synergy between aviation and technology. From humble beginnings to cutting-edge automation, FMCs have transformed the way aircraft navigate the skies, making air travel safer, more efficient, and more environmentally conscious.

CP JOIS

Human Factors

Tiger teams have been long used for problem-solving and or responding to opportunities (Laakso et al., 1999). Tiger teams are not just another form of a team with a set of resources. They are formed differently, used for episodic actions, and then released when the task is complete. In most cases, tiger teams are used for solving difficult problems in a timely way. Given this reason. these teams are formed with a purpose and bring specific skills (Pavlak, 2004). They are also created to self-sufficient and complete in terms of skills and capacity.

As a manager researching flight management system (FMS) issues, I would bring a group of resources with the required skill sets and more importantly experience. The skills needed would include, hardware, software programming, testing, and automation. I would also include subject matter experts from flight control, navigation, avionics, navigation data, and computational expertise. The team will also comprise resources from external partners for hardware, the operating system, and any other sub-components that were externally sourced. I would also ensure that escalation paths are clearly identified within each of the external organizations in case, such escalations were required to ensure priority and timeliness in those organizations.

Once the team has been formed, interaction cadence is important. When and where will they meet, how often and who leads the team – becomes important. Establishing a team leader helps with this process. Setting up a ‘war room’ will be essential to collate all the necessary design artifacts and incident reports. that will help troubleshoot the issue. A flight management system simulator will be required and set up. The simulator will help in reproducing the navigation guidance issue(s).

Robust system design “ensures that future systems continue to meet user expectations despite rising levels of underlying disturbances” (Mitra, 2010). The intent of the robust design is to allow a system to function reliably, perhaps with reduced capability, despite errors in input or computation. Systems are designed to accommodate a vast range of operating conditions and inputs. Despite that, every system has its limits where outside of that operating envelope, the system does not have the intelligence to handle the situation (Atkins et al., 2006). In the given FMS situation, without more detail, it’s hard to conclude that the system is either robust or not. Regardless of how holistic and intelligent a system is, once outside of its programmed boundary, the system would not know how to handle a specific problem. In 2008, Qantas flight 72 suffered an uncommanded loss in altitude now associated with a bit being flipped in the flight management system caused by ionization radiation (See Baraniuk, 2022 for more information on computer bit flips due to solar radiation associated solar flares). This is an example of ‘yet to be known’ factors that could impact the robustness of a system.

Typically redundancy is used as a mitigation for safety-critical systems. Having backup systems is an effective strategy for dealing with insufficient robustness (Mitra, 2010). Multiple of input sensors allow for differentiation models to detect differences and when supplemented with a tertiary sensor, allow for triangulation and therefore detection of an impending problem (Bijjahalli et al., 2020). In the case of software systems, where complex logic can be the cause for errors, exhaustive testing of all code branches and automated testing of multiple-programmatic paths is typically used to prevent an isolated line of code to cause an error (Huhns, & Holderfield, 2002). Data is another cause for the lack of robust behavior because systems are as precise as the data provided. Data verification and validation are the mitigation for this cause.

Ideally, it is best to build systems such that if it’s unable to compute an answer within its defined operating envelope, it must signal such failure to the crew and allow them to resolve the situation. That said, differential input computations led to the autopilot on Air France 447 disconnecting at 35000 feet over the Atlantic leaving the plane in the crew’s hands (Admiral Cloudberg, 2021). In the final analysis, the crew stalled the airplane and all data indicates that the controls were held in high pitch position all the way to its final impact. This indicates that using reverting to manual control as a means of robust design may also not be the best answer for all situations.

Human input is a common problem and protecting a system from erroneous input is perhaps the most significant challenge for designers (Atkins et al., 2006). To anticipate the various inputs that numerous users of a system could potentially input into a system is an extraordinary challenge for any designer. American Airlines flight 965 to Cali, Colombia impacted terrain from an erroneous input into the FMS (Ladkin, 1996). Rushing through an approach at an airport without operational radar, accepting a different approach than earlier planned and programmed, clearing the programming from the FMS to execute a visual approach, and rushing through FMS waypoint entry without verification with associated charts are reported to be the most probably causes (Pérez-Chávez & Psenka, 2001). There are more causes that came together as explained in Reason’s Swiss cheese model that contributed to the crash (Reason et al., 2006). Other factors included a single letter identification for a navaid 150 miles away which with some diligence and attention, could have been easily detected if the crew was not rushing. A single letter – R – indicating two different navaids ROMEO and ROZO – caused the airplane to make a sharp left turn and head straight into the terrain. Preventing error input is typically used to maintain the operational boundaries of a system. However, this could prove limiting in itself.

The first task for the team will be to reduce the errors as much as possible. This allows for a close study of the problem. Documenting the causes in fishbone diagrams allows for listing all causes that could have led to the issues. Taking each case individually to further resolve them would lead to resolution of the issue. The benefit of using a tiger team for this purpose is to have undistracted bandwidth to focus on the issues on hand.
There is no perfect answer to designing robust behavior. It is as much art as it is a science to build a complex, comprehensive design. Achieving perfect design is an ongoing challenge and it is worthy of mention that automation and human factors issues remain a serious concern for the aviation industry even today.

References:
Admiral Cloudberg. (2021, October 9). The Long Way Down: The crash of Air France flight 447. Medium; Medium. https://admiralcloudberg.medium.com/the-long-way-down-the-crash-of-air-france-flight-447-8a7678c37982Links to an external site.
Atkins, E. M., Portillo, I. A., & Strube, M. J. (2006). Emergency Flight Planning Applied to Total Loss of Thrust. Journal of Aircraft, 43(4), 1205–1216. https://doi.org/10.2514/1.18816Links to an external site.
Baraniuk, C. (2022, October 12). The computer errors from outer space. Bbc.comLinks to an external site.; BBC. https://www.bbc.com/future/article/20221011-how-space-weather-causes-computer-errorsLinks to an external site.
Bijjahalli, S., Sabatini, R., & Gardi, A. (2020). Advances in intelligent and autonomous navigation systems for small UAS. Progress in Aerospace Sciences, 115, 100617.
Huhns, M. N., & Holderfield, V. T. (2002). Robust software. IEEE Internet Computing, 6(2), 80-82.
Ladkin, P. (1996). AA965 Cali accident report. University of Bielefeld.
Laakso, M., Takanen, A., & Röning, J. (1999, June). The Vulnerability Process: a tiger team approach to resolving vulnerability cases. In Proc. 11th FIRST Conf. Computer Security Incident Handling and Response.
Mitra, S. (2010). Robust System Design. 2010 23rd International Conference on VLSI Design, 434–439. IEEE. https://doi.org/10.1109/VLSI.Design.2010.77Links to an external site.
Pavlak, A. (2004). MODERN TIGER TEAMS.
Pérez-Chávez, A., & Psenka, C. (2001). Systems accidents and epistemological limitations: The case of American airlines’ flight 965 in Cali, Colombia. Practicing anthropology, 23(4), 33-38.
Reason, J., Hollnagel, E., & Paries, J. (2006). Revisiting the Swiss cheese model of accidents. Journal of Clinical Engineering, 27(4), 110-115.
Pavlak, A. (2004). Modern TIger Teams.