Systems Engineering Design of an Electronically Interactive Application for Runway Incursion Prevention

Runway Incursion is the leading cause of serious incidents or accidents in airports. One of the most common causes of a runway incursion is airport unfamiliarity. Therefore, the researcher designed an electronically interactive application as a practice tool for pilots to utilize during flight preparation. The objective of this application is to enhance airport familiarity to ultimately reduce runway incursion. This application is interactive, affordable, accessible, and mobile device-based. It was designed using the Systems Engineering approach, following Human Factors Engineering principles to make this application user-friendly and to provide optimized human machine interaction. A model-based Systems Engineering software-CORE was utilized to manage the system requirements and provide clear traceability and rationality for each function. A prototype of the interface was developed and evaluated using a heuristic evaluation approach. The experts participating in the evaluation generally agreed that this application would provide an enhanced learning experience of the airport environment during flight preparation rather than studying the FAA airport diagram alone. This project provides a guideline for Software engineers to program this application expeditiously with the least amount of confusion

Developing an Integrated Rural Tourism Model for Stakeholders in Yuanjia Village, China

This research aims to propose an Integrated Rural Tourism (IRT) development model for stakeholders in Yuanjia village, China. Although IRT has been widely discussed, research rarely details effective approaches to developing IRT. Therefore, this study utilizes Yuanjia village as a research site to develop an IRT model, conducting a mixed methods approach. The research firstly explores well-designed CSR initiatives for tourism enterprises to promote IRT. Additionally, as successful IRT development requires stakeholders to develop shared institutional logic to take collaborative actions, the research explores the institutional logic guiding the behaviors of stakeholders in China’s rural tourism and further examines its relationship with IRT development. The findings show that stakeholders can promote IRT through implementing the proposed CSR initiatives and developing the identified institutional logic. Theoretically, this study contributes to the localization of the IRT concept in the context of China in accordance with its unique institutional features. Practically, the proposed model provides stakeholders with effective guidance to develop IRT successfully

Information-Coupled Turbo Codes for LTE Systems

We propose a new class of information-coupled (IC) Turbo codes to improve the transport block (TB) error rate performance for long-term evolution (LTE) systems, while keeping the hybrid automatic repeat request protocol and the Turbo decoder for each code block (CB) unchanged. In the proposed codes, every two consecutive CBs in a TB are coupled together by sharing a few common information bits. We propose a feed-forward and feed-back decoding scheme and a windowed (WD) decoding scheme for decoding the whole TB by exploiting the coupled information between CBs. Both decoding schemes achieve a considerable signal-to-noise-ratio (SNR) gain compared to the LTE Turbo codes. We construct the extrinsic information transfer (EXIT) functions for the LTE Turbo codes and our proposed IC Turbo codes from the EXIT functions of underlying convolutional codes. An SNR gain upper bound of our proposed codes over the LTE Turbo codes is derived and calculated by the constructed EXIT charts. Numerical results show that the proposed codes achieve an SNR gain of 0.25 dB to 0.72 dB for various code parameters at a TB error rate level of $10^{-2}$, which complies with the derived SNR gain upper bound.Comment: 13 pages, 12 figure

Specialist or Generalist? Instruction Tuning for Specific NLP Tasks

The potential of large language models (LLMs) to simultaneously perform a wide range of natural language processing (NLP) tasks has been the subject of extensive research. Although instruction tuning has proven to be a data-efficient method for transforming LLMs into such generalist models, their performance still lags behind specialist models trained exclusively for specific tasks. In this paper, we investigate whether incorporating broad-coverage generalist instruction tuning can contribute to building a specialist model. We hypothesize that its efficacy depends on task specificity and skill requirements. Our experiments assess four target tasks with distinct coverage levels, revealing that integrating generalist instruction tuning consistently enhances model performance when the task coverage is broad. The effect is particularly pronounced when the amount of task-specific training data is limited. Further investigation into three target tasks focusing on different capabilities demonstrates that generalist instruction tuning improves understanding and reasoning abilities. However, for tasks requiring factual knowledge, generalist data containing hallucinatory information may negatively affect the model's performance. Overall, our work provides a systematic guide for developing specialist models with general instruction tuning. Our code and other related resources can be found at https://github.com/DavidFanzz/Generalist_or_Specialist.Comment: Accepted to EMNLP 202

Will ocean acidification affect the digestive physiology and gut microbiota of whelk *Brunneifusus ternatanus*?

To understand the physiological responses of the Brunneifusus ternatanus to future ocean acidification (OA), histology, enzyme activity and gut bacterial composition at different pH levels (Control : C group, pH 8.1; Exposure period : EP group, pH 7.3) for 28 days were studied under laboratory conditions. Microbiota composition was analyzed using 16S rRNA gene amplicon sequencing. Enzyme activities of trypsin (TRY), lipase (LPS), amylase (AMS), and lysozyme (LZM) were used as biochemical indicators, as well as weight gain rate (WGR), specific growth rate (SGR) as growth indicators. The stress caused by OA resulted in alterations to the intestine, including partially swollen and degranulated enterocytes and rough endoplasmic reticulum (RER). The relative abundance of the core phylum in the acidified group changed significantly, showing an increase in Tenericutes and a decrease in Proteobacteria. Firmicutes/Bacteroides ratio declined from 4.38 in the control group to 1.25 in the EP group. We found that the enzymes TRY, LPS, and AMS activities were inhibited at reduced pH, which was positively correlated with the dominant genera Mycoplasma and Bacteroides; while LZM activities showed a significant increment, but showing a strong negative correlation. Furthermore, both WG and SRG values showed a depression at low pH lever. These results suggest that if anthropogenic CO2 emissions continue to accelerate, OA could lead to a negative impact on the whelk health, also compromising their growth performance and even survival. These findings will benefit the future risk assessments of OA or other related emerging environmental issue

EmotionPrompt: Leveraging Psychology for Large Language Models Enhancement via Emotional Stimulus

Large language models (LLMs) have achieved significant performance in many fields such as reasoning, language understanding, and math problem-solving, and are regarded as a crucial step to artificial general intelligence (AGI). However, the sensitivity of LLMs to prompts remains a major bottleneck for their daily adoption. In this paper, we take inspiration from psychology and propose EmotionPrompt to explore emotional intelligence to enhance the performance of LLMs. EmotionPrompt operates on a remarkably straightforward principle: the incorporation of emotional stimulus into prompts. Experimental results demonstrate that our EmotionPrompt, using the same single prompt templates, significantly outperforms original zero-shot prompt and Zero-shot-CoT on 8 tasks with diverse models: ChatGPT, Vicuna-13b, Bloom, and T5. Further, EmotionPrompt was observed to improve both truthfulness and informativeness. We believe that EmotionPrompt heralds a novel avenue for exploring interdisciplinary knowledge for humans-LLMs interaction.Comment: Work in progress; 9 page

Multi-scale Models for Transportation Systems Under Emergency Conditions

The purpose of this study is to investigate human behavior in emergencies. More specifically, agent-based simulation and social force models were developed to examine the impact of various human and environmental factors on the efficiency of the evacuation process, through a series of case studies. The independent variables of the case studies include the number of exits, the number of passengers, the evacuation policies, and instructions, as well as the queue configuration and wall separators. The results revealed the location of the exits, number of exits, evacuation strategies, and group behaviors all significantly impact the total time of the evacuation. For the queue configuration, short aisles lower infection spread when rope separators were used. The findings provide new insights in designing layout, planning, practice, and training strategies for improving the effectiveness of the pedestrian evacuation process under emergency

The Relationship Between Belief In A Just World And Spiritual Faith in the context of cross-cultural

So far, the researches about belief in a just world (BJW) have obtained many achievements in the fields of the behavior of punishing the victim, and the fimctions of building psychological well-being. There are researches indicated that there are links between religion and BJW, especially with Ultimate Justice(Begue, 2002). But to the people who don 1 have a religion, which support his or her sense of BJW? So we use the participants from China, which don't have religion, and the participants from Indonesia, which are all religion believer to find the answer. The result shows that, both participants from the two countries have the same level of general BJW and social belief, while the Immanent and Ultimate BJW, supernatural and pragmatic belief." the Indonesian participants score higher than Chinese participants. To the relationship between BJW and spiritual faith, Chinese participants' BUJ and general BJW are connected with social belief, while the Indonesian part shows the general BJW and Ultimate BJW are corresponded with all belief, and the Immanent BJW is related with Pragmatic Belief and Social Belief The scales we apply are the Just Word scale(Rubin& Peplau,I973) and Belief in Immanent/Ultimate Justice Scale(Maes, 1999), both have good validity and reliability; and the scale of spiritual belief (Song Xingchuan, 2004) to find out the difference between Indonesian and Chinese students, and we also use the classical "trolley problem", which is added the variable of obey or violate the norm, to estimate the extend of one concern about the social norm