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Neuro Linguistic Programming (NLP) is a collection of techniques for personality development. Meta programmes, which are habitual ways of inputting, sorting and filtering the information found in the world around us, are a vital factor in NLP. Differences in meta programmes result in significant differences in behaviour from one person to another. Personality types can be recognized through utilizing and analysing meta programmes. There are different methods to predict personality types based on meta programmes. The Myers–Briggs Type Indicator® (MBTI) is currently considered as one of the most popular and reliable methods. In this study, a new machine learning method has been developed for personality type prediction based on the MBTI. The performance of the new methodology presented in this study has been compared to other existing methods and the results show better accuracy and reliability. The results of this study can assist NLP practitioners and psychologists in regards to identification of personality types and associated cognitive processes.

Understanding personality traits can help individuals reach their full potential and has applications in various fields such as recruitment, advertising, and marketing. A widely used tool for assessing personality is Myers-Briggs type indicator (MBTI). Recent advancements in technology have allowed for research on how personalities can change based on social media use. Previous research used machine learning methods, deep learning methods, until transformers-based method. However, these previous approaches must be revised to require extensive data and a high computational load. Although transformer-based methods like bidirectional encoder representations from transformers (BERT) excel at understanding context, it still has limitations in capturing word order and stylistic variations. Therefore, this study proposed integrating fine-tuning BERT with recurrent neural networks (RNNs) consisting of vanilla RNN, long short-term memory (LSTM), and gated recurrent unit (GRU). This study also uses a BERT base fully connected layer as a comparison. The results show that the BERT base fully connected layer approach strategy has the best evaluation results in class extraversion/introversion (E/I) of 0.562 and class feeling/thinking (F/T) of 0.538. then, the BERT+LSTM approach strategy has the highest accuracy for the intuition/sensing (N/S) class of 0.543 and judging/perceiving (J/P) of 0.532. 

Indigo carmine is a commonly used industrial blue dye. To determine its concentration in a commercially available food dye composed of a mixture of indigo carmine and D-glucose, this paper characterizes it through (ATR, KBr) FTIR micro-Raman as well as UV/Vis and clock: Briggs–Rauscher (BR) oscillatory reaction methods. The indigo carmine was detected in the bulk food dye only by applying micro-Raman spectroscopy, indicating a low percentage of the indigo carmine present. This research provides an improvement in the deviations from the experimental Raman spectrum as calculated by the B97D/cc-pVTZ level of theory one, resulting in a better geometrical optimization of the indigo carmine molecule compared to data within the literature. The analytical curves used to determine indigo carmine concentrations (and quantities) in an aqueous solution of food dye were applied by means of UV/Vis and BR methods. BR yielded significantly better analytical parameters: 100 times lower LOD and LOQ compared to commonly used UV/Vis. The remarkable sensitivity of the BR reaction towards indigo carmine suggests that not only does indigo carmine react in an oscillatory reaction but also its decomposition products, meaning that the multiple oxidation reactions have an important role in the BR’s indigo carmine mechanism. The novelty of this research is the investigation of indigo carmine using a clock BR reaction, opening new possibilities to determine indigo carmine in other complex samples (pharmaceutical, food, etc.).

This study examines the relationship between speech characteristics and personality traits by drawing on pseudo-naturalistic conversations and on personality dimensions identified by the Myers–Briggs Type Indicator (MBTI) model which assesses four personality dimensions of introversion-extroversion, sensing-intuiting, thinking-feeling, and judging-perceiving. The speech of 30 participants was recorded and transcribed, after which a number of speech features including pitch, loudness, response time (i.e., how fast one responds to a prompt), speech rate, and discourse markers were extracted and analyzed. Results show that several speech features correspond to different personality dimensions. Specifically, speech rate as measured by words per minute reveals significant differences between judging individuals and perceiving individuals (perceiving individuals speak faster than judging individuals); there is a significant difference in response time for extroverts and introverts (extroverts respond faster); a significant difference is observed in loudness between judging and perceiving individuals (judging individuals are louder). The frequency of discourse markers is significantly higher for intuiting individuals than sensing individuals. The study discusses these findings in further inquiring the relationship between language and personality.

The Myers-Briggs Type Indicator (MBTI) is a well-known personality test that assigns a personality type to a user by using four traits dichotomies. For many years, people have used MBTI as an instrument to develop self-awareness and to guide their personal decisions. Previous researches have good successes in predicting Extraversion-Introversion (E/I), Sensing-Intuition (S/N) and Thinking-Feeling (T/F) dichotomies from textual data but struggled to do so with Judging-Perceiving (J/P) dichotomy. J/P dichotomy in MBTI is a non-separable part of MBTI that have significant inference on human behavior, perception and decision towards their surroundings. It is an assessment on how someone interacts with the world when making decision. This research was set out to evaluate the performance of the individual features and classifiers for J/P dichotomy in personality computing. At the end, data leakage was found in dataset originating from the Personality Forum Café, which was used in recent researches. The results obtained from the previous research on this dataset were suggested to be overly optimistic. Using the same settings, this research managed to outperform previous researches. Five machine learning algorithms were compared, and LightGBM model was recommended for the task of predicting J/P dichotomy in MBTI personality computing.

In recent years, the rapid expansion of online learning content has made it increasingly difficult for students to identify suitable educational pathways. This challenge is particularly significant for engineering students, who often require structured guidance to select appropriate academic courses. To address this issue, an intelligent recommendation model is proposed that assists students in discovering the most suitable academic path based on their personal background and personality traits. A hybrid optimization-based deep recurrent neural network (DRNN) with Myers-Briggs Type Indicator (MBTI) is presented for Recurrent Academic Path Recommendation (RAPR) for engineering students. At first, the data transformation is applied considering the log kernel to improve data quality. Then, the Sparse Fuzzy C-Means Clustering (Sparse FCM) is employed to choose imperative features. At last, an adaptive recommendation of the engineering department is performed using DRNN, which is trained based on the Magnetic Invasive Weed Optimization (MIWO) algorithm. On the other hand, MBTI personality type categorization is done, wherein the correlation of courses with MBTI outcome is detected using MIWO-based DRNN. The evaluation is conducted using two datasets, which are the collected academic information of students from Kerala and Tamilnadu. These datasets include the details, such as students’ personality traits, Science, Technology, Engineering, and Mathematics performance, extra-curricular involvement, MBTI weight test, and MBTI score. The performance of the proposed MIWO-based DRNN is evaluated using precision, recall, and F-measure metrics and the proposed method offers the best performance with the highest precision of 0.900, recall of 0.900, and F-measure of 0.899, demonstrating its effectiveness in accurately recommending academic paths for engineering students.

PurposeThe purpose of this paper is to extend the research domain of Sales & Operations Planning (S&OP) beyond the hard issues by focusing on soft issues in S&OP processes. This paper aims to investigate how consciousness of different personality types can affect S&OP processes.Design/methodology/approachThis paper is based on a single longitudinal case study from a medium-sized enterprise with a data collection period of more than two years. This paper is based on observation and interviews gathered at several stages during pilot implementation and operation phases.FindingsThis paper indicates that a focus on behavior using personality type theory and key behavioral indicators has provided a common framework for understanding how the S&OP process is impacted by different personalities and behavior. This knowledge has increased the awareness of which behavior sustains a silo mentality and which behavior breaks it down. Quotations are used to provide substance of this explorative topic.Research limitations/implicationsAs a single case study, this paper only provides results for analytical generalization.Practical implicationsConsciousness of behavioral elements in S&OP processes is proposed here as a complement to key performance indicators as levers to implement and obtain sustained operation of S&OP.Originality/valueThis paper is the first explicitly integrating personality type theory for a better understanding of implementing and operating S&OP processes. This paper contributes with a new understanding of S&OP success factors and how a common language may improve process efficiency.

CEO/President/Entrepreneur and all-around innovative leader Cynthia Cleveland tells us the story of the remarkable mother-daughter team who created the single most impactful personality test ever designed. Still used world-wide by both major corporations and individuals, The Myers-Briggs instrument makes Jung’s personality types understandable and useful in people’s lives. The idea came from the mother, Katharine Briggs, then the daughter, Isabel Briggs-Myers, built it into a reality… devising a tool that has lasted for decades, helping people understand who they are and how to work together. What type are you???

In the midst of World War II's turmoil, the quaint British town of Bury St. Edmonds becomes a focal point where lives intersect and secrets unravel. An 18-year-old woman, finds herself caught in the throes of a great wartime secret – the breaking of the German Enigma code. Her recruitment into the \"Ultra\" program brings her to the heart of Bletchley Park's most clandestine operations, where Alan Turing and his team forge the world's first computer in a bid to crack the ever-changing German codes. Every day, she grapples with the weight of the secret, which is so profound that even her family is oblivious to her covert role. Meanwhile, amidst the dances and interactions in the town, she captures the heart of an assertive American soldier. Their whirlwind wartime romance culminates in a heartwarming union, facing the challenges of the Official Secrets Act that surrounds her duty. The soldier, persistent and deeply in love, goes to great lengths, even penning letters to officials, in order to secure her release from the program and to solidify their commitment to one another. They eventually marry and cross the Atlantic to build a new life in the US, where they raise children who, years later, come to discover the incredible stories of their parents' contributions during the tumultuous war years.

New media and new applications of existing media are typically seen as ways of distributing knowledge more effectively, often with hopes that this process will strengthen democracy. Adopting a history-ofknowledge approach, the authors analyze methods of knowledge circulation attending early print, nineteenth-century mechanics' institutes and public libraries, early radio broadcasting, and explanatory journalism, providing a comparative historical framework for a recent new-media platform for distributing knowledge, The Conversation network. Appealing to a socially broad audience has consistently been a challenge. Efforts to distribute knowledge also reflected differences in prevailing media ecosystems, national systems of political economy, and contemporary social/political concerns.