Feedback from 50 operators on digitalizing their business

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Needs, ambitions, expectations and disappointments by Capt. Jan Wilhelmsson, Vice President, Commercial Shipping, Eniram (a Wärtsilä company)

Feedback from 50 operators on
digitalizing their business
Needs, ambitions, expectations and disappointments

Simplified into 3 categories
SATISFIED OPERATORS –
successful in digitalizing their
vessel operations and business
UNSATISFIED OPERATORS – have
moved ahead with digitalization but are
not satisfied with the outcome or have
received return of investment
NON-ENGAGED OPERATORS
– Have no interest in engaging
in new technology and rely on
traditional methods

Different Industries – Different progress
CRUISE AND CONTAINER INDUSTRY
• Early adopters
• Owner-Operator structure mainly
• Fleet Operations Centre
• Container industry generally claim to
have saved 3-5% due to real- time
monitoring alone.
WET & DRY BULK INDUSTRY
• Different Business Model
• Traditional thinking
• Exceptions confirming the rule
• “Principal agent problem” hampering
digitalisation with no capex justification

What have the satisfied
operators in common?
• A strong engagement and interests from top
management to move ahead with
technology
• Involvement from subject matter experts
• An appropriate timeline is given to execute
• Digitalisation not run as a normal IT project,
more a long term involvement from the
whole business
• Proper focus and recourses given towards
data quality, i.e. filtering, enriching modelling
and validation.

Where do the unsatisfied operators fail?
We spent a lot of money to
build this system years
ago so we are done. (Or
stuck with it)
”
We did this years ago,
we now have all this
data, but it’s so broken
we can’t do anything
with it.
Failure to appoint
project teams that
can and will take the
time to engage
“Not invented here”
philosophy
”
”
”

• The belief that the business model is so
unique and complex that it isn’t possible to
automatize it.
• Their operations is different from other
operations so that automatized solutions
aren’t not relevant
• Let other pave the way and get on board
once it has been tested and verified
Why do some operators not
engage in digitalization?

CUSTOMER
Easy-to-install autonomous
battery powered transponder
CLOUD
DELIVERY
“Fleet” Software
+ Reports:
• C/P Monitoring
• Norm. Fuel Cons
• Speed Perf.
(additional reporting
sold separately)
ENIRAM
DATA CENTER
COMBINE AND ENRICH
L-Band 5 minutes point data
from SkyLight transponder
Noon reports via
email directly to data
center for consumption
Details.
METEOROLOGICA
L
DATA
DATA
MODELING
COLLECTING DATA
Developing a product based on the
feedback and 12 years experience of
performance monitoring -
Eniram
SKYLIGHT

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The rapid advancements in artificial intelligence and natural language processing have significantly transformed human-computer interactions. This thesis presents the design, development, and evaluation of an intelligent chatbot capable of engaging in natural and meaningful conversations with users. The chatbot leverages state-of-the-art deep learning techniques, including transformer-based architectures, to understand and generate human-like responses. Key contributions of this research include the implementation of a context- aware conversational model that can maintain coherent dialogue over extended interactions. The chatbot's performance is evaluated through both automated metrics and user studies, demonstrating its effectiveness in various applications such as customer service, mental health support, and educational assistance. Additionally, ethical considerations and potential biases in chatbot responses are examined to ensure the responsible deployment of this technology. The findings of this thesis highlight the potential of intelligent chatbots to enhance user experience and provide valuable insights for future developments in conversational AI.

Unblocking The Main Thread - Solving ANRs and Frozen Frames

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In the realm of Android development, the main thread is our stage, but too often, it becomes a battleground where performance issues arise, leading to ANRS, frozen frames, and sluggish Uls. As we strive for excellence in user experience, understanding and optimizing the main thread becomes essential to prevent these common perforrmance bottlenecks. We have strategies and best practices for keeping the main thread uncluttered. We'll examine the root causes of performance issues and techniques for monitoring and improving main thread health as wel as app performance. In this talk, participants will walk away with practical knowledge on enhancing app performance by mastering the main thread. We'll share proven approaches to eliminate real-life ANRS and frozen frames to build apps that deliver butter smooth experience.

Analysis and Design of Algorithm Lab Manual (BCSL404)

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Profiling of Cafe Business in Talavera, Nueva Ecija: A Basis for Development ...

IJAEMSJORNAL

This study aimed to profile the coffee shops in Talavera, Nueva Ecija, to develop a standardized checklist for aspiring entrepreneurs. The researchers surveyed 10 coffee shop owners in the municipality of Talavera. Through surveys, the researchers delved into the Owner's Demographic, Business details, Financial Requirements, and other requirements needed to consider starting up a coffee shop. Furthermore, through accurate analysis, the data obtained from the coffee shop owners are arranged to derive key insights. By analyzing this data, the study identifies best practices associated with start-up coffee shops’ profitability in Talavera. These findings were translated into a standardized checklist outlining essential procedures including the lists of equipment needed, financial requirements, and the Traditional and Social Media Marketing techniques. This standardized checklist served as a valuable tool for aspiring and existing coffee shop owners in Talavera, streamlining operations, ensuring consistency, and contributing to business success.

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Literature Reivew of Student Center Design

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It was back in 2020, during the COVID-19 lockdown Period when we were introduced to an Online learning system and had to carry out our Design studio work. The students of the Institute of Engineering, Purwanchal Campus, Dharan did the literature study and research. The team was of Prakash Roka Magar, Priyanka Karn (me), Riwaz Upreti, Sandip Seth, and Ujjwal Dev from the Department of Architecture. It was just a scratch draft made out of the initial phase of study just after the topic was introduced. It was one of the best teams I had worked with, shared lots of memories, and learned a lot.

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Development of Chatbot Using AI/ML Technologies

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Feedback from 50 operators on digitalizing their business

1. Feedback from 50 operators on digitalizing their business Needs, ambitions, expectations and disappointments

2. Simplified into 3 categories SATISFIED OPERATORS – successful in digitalizing their vessel operations and business UNSATISFIED OPERATORS – have moved ahead with digitalization but are not satisfied with the outcome or have received return of investment NON-ENGAGED OPERATORS – Have no interest in engaging in new technology and rely on traditional methods

3. Different Industries – Different progress CRUISE AND CONTAINER INDUSTRY • Early adopters • Owner-Operator structure mainly • Fleet Operations Centre • Container industry generally claim to have saved 3-5% due to real- time monitoring alone. WET & DRY BULK INDUSTRY • Different Business Model • Traditional thinking • Exceptions confirming the rule • “Principal agent problem” hampering digitalisation with no capex justification

4. What have the satisfied operators in common? • A strong engagement and interests from top management to move ahead with technology • Involvement from subject matter experts • An appropriate timeline is given to execute • Digitalisation not run as a normal IT project, more a long term involvement from the whole business • Proper focus and recourses given towards data quality, i.e. filtering, enriching modelling and validation.

5. Where do the unsatisfied operators fail? We spent a lot of money to build this system years ago so we are done. (Or stuck with it) ” We did this years ago, we now have all this data, but it’s so broken we can’t do anything with it. Failure to appoint project teams that can and will take the time to engage “Not invented here” philosophy ” ” ”

6. • The belief that the business model is so unique and complex that it isn’t possible to automatize it. • Their operations is different from other operations so that automatized solutions aren’t not relevant • Let other pave the way and get on board once it has been tested and verified Why do some operators not engage in digitalization?

7. CUSTOMER Easy-to-install autonomous battery powered transponder CLOUD DELIVERY “Fleet” Software + Reports: • C/P Monitoring • Norm. Fuel Cons • Speed Perf. (additional reporting sold separately) ENIRAM DATA CENTER COMBINE AND ENRICH L-Band 5 minutes point data from SkyLight transponder Noon reports via email directly to data center for consumption Details. METEOROLOGICA L DATA DATA MODELING COLLECTING DATA Developing a product based on the feedback and 12 years experience of performance monitoring - Eniram SKYLIGHT

8. Eniram SKYLIGHT 2.0 Key Features ENIRAM FLEET EXPLORATION TOOL • Predictive analysis and proactive planning with Eniram’s fleet ENIRAM REPORTING • Charter Party monitoring, Normalised fuel-curve and Speed profile report MRV • SkyLight can help with the monitoring and reporting of C02 emissions Pre-Requisites: • Eniram transponder • Eniram Fleet Software Eniram SKYLIGHT 2.0

Feedback from 50 operators on digitalizing their business

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