Reviewerly/exHarmony huggingface dataset:
Semantic Segmentation under Adverse Conditions: A Weather and Nighttime-aware Synthetic Data-based Approach

Recent semantic segmentation models perform well under standard weather conditions and sufficient illumination but struggle with adverse weather conditions and nighttime. Collecting and annotating training data under these conditions is expensive, time-consuming, error-prone, and not always practical. Usually, synthetic data is used as a feasible data source to increase the amount of training data. However, just directly using synthetic data may actually harm the model's performance under normal weather conditions while getting only small gains in adverse situations. Therefore, we present a novel architecture specifically designed for using synthetic training data for domain adaptation. We propose a simple yet powerful addition to DeepLabV3+ by using weather and time-of-the-day supervisors trained with multi-task learning, making it both weather and nighttime aware, which improves its mIoU accuracy by $14$ percentage points on the ACDC dataset while maintaining a score of $75\%$ mIoU on the Cityscapes dataset. Our code is available at https://github.com/lsmcolab/Semantic-Segmentation-under-Adverse-Conditions.
دافعية الاتقان لدى تدريسي اقسام علوم الحياة

The aim of the research is to identify the mastery motivation among the teaching of biology departments. The research was determined by teaching the biology departments in the universities (Al-Qadisiyah, Kufa, Babylon, Karbala, Al-Muthanna), and for the academic year (2021-2022). The descriptive research method was adopted, and the sample size was (187) Teaching and teaching in the departments of biology, were chosen randomly. The two researchers prepared a tool to achieve the objectives of the research. It is a measure of mastery motivation, which in its final form consisted of (30) items, and the items were divided into five areas according to the theory of (1990 et al &amp; Morgan). The stability of the scale using Cronbach’s alpha coefficient, whose value is (). The research tool was applied, and the data was statistically analyzed and processed using Microsoft Excel, and the Statistical Portfolio for Social Sciences (SPSS) program, and the following results were reached. Also, there are no statistically significant differences attributable to gender, and there are no statistically significant differences attributed to the scientific title, and based on the results that have been reached, the researchers present a set of recommendations Key words: Mastery motivation , Department teacher of biology
Design and implementation of small private cloud system with highly reliable management and monitoring

In order to improve the use efficiency of university laboratory information resources, strengthen the smooth progress of teaching and research tasks and ensure the reliability of private cloud, this paper proposes a deployment and monitoring scheme of private cloud system with highly reliable software and hardware resources, in which the monitoring scheme is highlighted. Adopt virtualization and other key technologies to ensure the reliability of physical host and virtualized environment. The deployment of a small private cloud platform composed of 6 hosts and equipped with high-capacity storage devices is realized, which can meet the daily teaching and research management needs of teachers and students in the laboratory. Taking ZABBIX as the framework, expand and improve its monitoring function, complete the fault detection and analysis of physical equipment, virtual resources and software applications of private cloud platform, focus on the monitoring of the hardware foundation layer, and realize the reliability monitoring of private cloud platform. The scheme takes the self-built private cloud of small laboratories in colleges and universities as the research subject and the open-source monitoring software as the means to realize the effective utilization and reliability assurance of resources. While meeting the requirements of daily teaching and research tasks of laboratories, the scheme is also applicable to the management and monitoring of self-built cloud of small and medium-sized enterprises.
The application of deep learning-based face recognition system in public safety

With the advancement of information technology, deep learning and face recognition technology is widely employed in financial transactions, public security management, employee attendance, and public security. Regarding the technical advantages of the recognition system, this paper first explains the demand of the age for the system, then studies the impact of deep learning on face recognition, and finally highlights the application path and future development direction of the face recognition system in public security for the reference of relevant personnel. The face recognition system upgraded by deep learning has increased personal information security and favorable influences public security management.
Suggestion of Digital Technology Application for the Acupoints Education in Korean Medicine

In the recent education market, Edutech technology, in which various digital technologies are grafted into the education, is being actively applied due to the 4th industrial revolution and the development of ICT. In particular, realistic experiential learning contents that can provide realistic and immersive learning in a virtual space are in the spotlight and are being expanded to each field. However, in the field of Korean medicine education, the introduction of ICT is delayed due to the nature of Korean medicine, difficulties in apprenticeship education, quantitative education, and the absence of an objective evaluation system. Therefore, in this study, we propose a digital technology application for acupuncture and acupuncture points, where practice is particularly important in Korean medicine. Various methods of acupuncture and acupoints education using AR, MR, IoT and Touch-Display Table will provide an opportunity to change the paradigm of Korean medicine education and further contribute to the globalization of Korean medicine.
Supervision as a form of inclusive education retraining and school community professional advancement

Using the example of Kryvyi Rih, we present the supervision model used to promote the education reform in Ukraine and the retraining of the school's major players. Through a sociopolitical and educational description of the current situation in Kryvyi Rih, empirical study has introduced a model of retraining. Due to this, 124 key stakeholders from 20 inclusive schools underwent testing to help plan the implementation of the monitoring model (teachers, tutors, staff, psychologists and parents from 7 districts of Kryvyi Rih were invited to participate). In this study, we provide an alternative strategy for interagency supervisory groups and communication, with an emphasis on the model supervision retraining of inclusive education specialists. Four stages make up the supervision process: case report, exchange, conceptualization, and summary. In the paper, we suggest a modification of an unstructured interview by a specialist who specifies the context of training supervision in order to facilitate successful work. The psycho-educational support team in inclusive education was able to propose the supervision program thanks to the analysis of the organizational, methodological, and information retraining system and the execution of the pilot project of supervisory groups: I. Providing team members with the necessary training to work with the objectives of each child development plan; II. Using case preparation tools; III. Analyzing environmental elements; and IV. Managing team support.
MERGE and Pair-Merge of Heads

Jae-Young Shim. 2022. MERGE and Pair-Merge of Heads. Studies in Modern Grammar 115, 1-26. Chomsky (2019a,b, 2020) reformulates the standardly assumed conception of Merge in terms of workspace, arguing that the operation only operates over syntactic objects placed in a workspace. Alongside this revised version of Merge, often referred to as ‘(capital) MERGE’ in the literature, he proposes a principle of Resource Restriction which, he claims, MERGE ought to meet. In this paper, I first review the workspace-based operation MERGE and present its empirical and conceptual advantages over its predecessor, Merge.&#x0D; I then examine the two proposals on pair-Merge of heads put forward in Chomsky (2015) and Epstein, Kitahara and Seely (2016) with discussions on their potential conceptual problems with respect to rule ordering and Anti-Locality. I further show that possible implementations of pair-Merge of heads in the MERGE-based system give rise to some new problems in terms of accessibility defined by Minimal Search. Finally, focusing on pair-MERGE of R and v*, I present an alternative analysis to resolve the addressed problems, arguing that the pair-merged structure of R and v* is generated, not in the course of derivation but inside the Lexicon via a merging process I call Lexical Merger, or l-merger.
A New Point Process Regression Extreme Model Using a Dirichlet Process Mixture of Weibull Distribution

The extreme value theory is widely used in economic and environmental domains, it aims to study the stochastic extreme behaviors associated with rare events. In this context, we consider a new mixture model for extremal events analysis, including a Dirichlet process mixture of Weibull (DPMW) distribution below the threshold and the point process (PP) extreme model for the upper tail. This model developed a regression structure for the PP extreme model parameters, which explains the variation of the exceedance through all tail parameters. The estimation of the model parameters is performed under the Bayesian paradigm, applying the Markov chains Monte Carlo (MCMC) method. The model is applied to both simulation and real environmental data to demonstrate the performance in extrapolating extreme events.
Design of Super Mario Game Using Finite State Machines

A finite state machine, commonly known as a finite state automaton, is a model of computation based on a theoretical machine and is composed of one or more states. It enables the switch between multiple possible states and modification of the behaviour according to the state. One of the widely used applications of finite automata is in the video gaming industry. Game designing is the methodology of developing the content and rules of a game in the initial stages. It involves designing the characters, rules, environment, action, and rewards. For example, Super Mario is a game series based on the fictional plumber Mario created by Nintendo. The fundamental purpose of the game is to move the character, Mario and complete as many stages as possible. The secondary goal is killing the enemies and collecting coins or additional items. This project involves Mario transforming his states and behaviour based on the events that have occurred using finite automata. This paper deals with implementing the Super Mario Game Design using Python Programming Language and JFLAP, a widespread open-source software tool used in the Formal Language and Automata courses.
Wearable Thong Entrenched with SoS Facility and Mobile Ad Hoc Network

To ensure peace and safety of the country, military forces are inevitable for the country’s protection. India has the second largest military force in the worlds with the strength of 1.4 million active troops. The army people lose their valuable lives due to lack of technical infrastructure to provide status about the injured soldiers. Many lose their lives and become disabilities because of injuries rather than battlefield. Nowadays, there are vast amount of electronic gadgets to fight against the enemies and secure the nation in the border. But in some adverse conditions like bad weather or due to remote location of soldiers, it becomes impossible to interact with them and monitor their health conditions of militants. In this work, we are developing a modern wearable smart thong entrenched with system of system facility and mobile ad hoc network. It has the special feature of continuously monitoring the health condition of troops. It also continuously records the health parameters and environmental parameters of the military warriors so that valuable lives of soldiers which is significant asset to our country can be rescued at right time.
Robust Cuckoo Search Enabled Fuzzy Neuro Symbolic Reasoning-Based Alzheimer’s Disease Prediction at Their Earlier Stages

The cognitive impairments among elderly peoples make their lifestyle more complex, and it is extremely essential to accurately discover patients with mild cognitive impairment stage as it may or may not progress to Alzheimer’s disease. Many machine learning models have developed to discover the prediction of Alzheimer’s disease, but they are constrained with imbalanced medical dataset with the disease case records. Thus, this paper concentrates on developing the robust model which handles the imbalanced data when there are a smaller number of instances with case label of dementia. In this work, neuro fuzzy symbolic reasoning is developed by adapting case-based reasoning to retrieve similar pattern of matched records with the new instance as input query to determine whether it suffers from dementia or not. The case-based reasoning is empowered by applying cuckoo search model, which involves searching for matching records by applying levy flight strategy to define unknown instances and their corresponding matching instance labels, and this information is given as input to the fuzzy artificial neural network along with training dataset to enhance its prediction accuracy. The FANN with the additional knowledge obtained from cuckoo search-enhanced case-based reasoning during training phase handles uncertainty and produces more accurate results for Alzheimer’s prediction compared to the other traditional models of classification. During testing phase, the new cases are predicted and if the output is correct, then it is added and maintained in the case history for future references. The simulation results proved the prominence of cuckoo search-enabled symbolic reasoning-based Fuzzy Neuro Classifier by applying this strategy on ADNI dataset.
Study on Later Life of Poor and Humble Scholars: Centered on Later Life of Mumyeongja Yun Ki andHis Response to Reality

In this study, later lives of ‘poor and humble scholars’, their emotions and their responses to reality are examined with the example of Mumyeongja Yun Ki.&#x0D; Yun Ki suffered from diseases including malaria due to senescence during his later life and to make matters worse, he had to endure severe pain from hearing impairment. The bridle of senescence and being from a poor and humble family was a stumbling block for him from the beginning of becoming a public official. He could not get the Cheong'yo-jik(淸要職) post and he was pained by the hard working as a lowest public official. Consequently, he was discontented. The poverty that molested his ancestors was not alleviated even after he became a public official. He expressed his emotions such as frustration, regret, resentment, grievance, self-deprecation, and moan about his later life in his poems in a straightforward way. He preserved his identity as he led a life filled with grumbles in an unjust world. Until the end of his life, he was destitute, which was also the result of his integrity and honesty.&#x0D; Yun Ki had the sense of identity that he was from the scholar family and strived to overcome the reality of being a poor and humble scholar. His integrity worked as an obstacle for his social relations. He had his principle and beliefs, which were not compatible with the world. However, he did not change his values and identity to gain worldly benefits. He was sensitive to calamity of slander, he continuously took precaution against his desire to speak out and its consequence of calamity of slander since his 50s. Furthermore, he declared to keep silence on matters after the long and careful consideration. It was the great decision to reveal his self-esteem and to preserve his family. The desire to reveal his identity was satisfied by his critical writing. His critical writing became the alternative to keeping silence, through which he faced the bitter reality and planned for the future.&#x0D; Yun Ki, expressed anguish, conflicts in his inner world, remorse, guilty conscience, anger and rebuke a lot but he assessed his life in a positive way. That is because he had self-respect that he did not meet the world halfway but preserved his integrity and identity.
The CreateML-based compared to the AutoML-based approach to animal image classification

Many platforms based on auto machine learning approaches have emerged as a result of the rapid development of machine learning. However, the performance differences between platforms have rarely been investigated. In this study, Google Cloud AutoML and Apple CreateML platforms are compared to find the difference in terms of the performance. To be more specific, we trained the model with the same dataset from Kaggle Animal 10. Three experiments are conducted between Google Cloud AutoML and Apple CreateML to achieve this goal. Finally, we arrived at the conclusion by examining the training accuracy, validation accuracy, and average precision across these two platforms. According to each pair of comparative tests, Google Cloud AutoML appears to perform better in every experiment when compared to Apple CreateML.
The Relationship among Self-efficacy for Group Work, Flow, Perceived Usefulness, and Acceptance of Software Education in Learning for Pre-service Early Childhood Teachers

Purpose: The purpose of this study is to investigate the relationship among self-efficacy for group work, perceived usefulness, flow, and acceptance of software education in a team-based software class for pre-service early childhood teachers.&#x0D; Methods: For this purpose, path analysis was conducted by collecting data from 116 pre-service early childhood teachers of the software courses opened in the second semester of 2020 and 2021. The proposed path model posited that self-efficacy for group work influenced flow, flow influenced perceived usefulness and acceptance of software education, and perceived usefulness influenced acceptance of software education.&#x0D; Results: As a result of the study, self-efficacy for group work influenced flow, and both flow and perceived usefulness influenced acceptance of software education, significantly and positively. Finally,flow indirectly influenced acceptance of software education.&#x0D; Conclusion: The implications of enhancing software education for pre-service early childhood teachers were discussed based on the findings.
The relationship between data utilization pattern and text quality in writing through the use of data generated by elementary school students

Purpose: The purpose of this study was to examine the source text used in text written by student authors and to check how it related to the quality of the text. Implications for writing education using data were also explored.&#x0D; Methods: An essay writing task using data was presented to 88 5th grade elementary school students and the results were evaluated. In addition, a T-unit analysis was performed with the data and texts produced by the students. Quantitative figures such as the number of quoted sentences, modified sentences, and adjacent sentences were calculated, and the correlation between the figures and text quality was analyzed.&#x0D; Results: The text quality was negatively correlated with the citation rate and positively correlated with the strain rate. The citation rate was correlated with organization among the sub-elements of the text query, and the transformation rate was correlated with the content and expression among the sub-elements of the text query. The citation rate showed a negative correlation with the total number of sentences, strain rate, and positive correlation with the number of adjacent sentences and number of texts.&#x0D; Conclusion: In a writing class, when material text is provided for the purpose of helping students to create content, it is necessary to instruct the students that the content of the material should be partially utilized. In addition, it is necessary to give specific examples of transforming and utilizing the contents of the data. Moreover, it is necessary to gradually transition from the stage of using a single text to the stage of using multiple texts.
Simulation of a polarization-transverse momentum hyperentangled photon source

The simulation and analysis of a hyperentangled photon source based on polarization and transverse momentum are achieved using the MATLAB platform. The analysis includes determining the emission pattern of a spontaneous parametric down-conversion source and the opening angles of emission cones and their dependence on wavelength. The energy conservation in the generation process and the correlations between the hyperentangled states are investigated. The results show that the generated states are maximally entangled, and Bell’s inequality test is proven to satisfy the theoretical limits. The proposed model gives better insight into the generation process of hyperentangled photons. It could be integrated with simulations of any arbitrary system based on a hyperentangled source.
Billion-Year Rewind Tracks Supercontinents and Mantle Structures

Scientists have traced past pathways of tectonic plates back a billion years using computer models, with intriguing results. Incorporating geologic data as a check on model output, however, has proven tricky.
Health, privacy and liberty: a call for digital governance during (and after) the pandemic

The COVID-19 pandemic has boosted the development and use of technology by increasing the use of previously existing technological resources, such as maps identifying population movements; assigning new uses to previously existing technological mechanisms, such as the use of facial recognition for monitoring infected people; and encouraging the development of new technologies, such as apps that ascribe risk codes to citizens. Without these digital measures, the pandemic would probably continue to expand, or, alternatively, entire populations would have to be quarantined for months (or even years), with significant consequences arising from either scenario. Technologies provide tools to avoid those scenarios. However, digital measures come at a price to our rights, namely our rights to privacy and liberty. Precautions and limitations ought to be imposed on the use of these technologies, forming a code of digital governance for COVID-19.
COVID-19, Webinars and human capital development among academics in higher education institutions

Though COVID-19 pandemic came with lockdowns that made it difficult for physical conferences, seminars, workshops, and lectures to be attended; yet it opened-up opportunities for virtual meetings. Barring challenges such as data cost and disruptions in internet accessibility, the absence of clear-cut guidelines for determining preferred virtual meetings by the appointments and promotions committees of Nigerian higher education institutions (HEIs) poses the dilemma of attendance at predatory ones by academics. This study utilised the interpretive research paradigm to unpack two assumptions and seven mutually inclusive criteria that could guide virtual learning platforms for human capital development in HEIs in Nigeria. The findings of this study are expected to trigger discourses as well as deliberate interventions on the criteria for e-conferences and webinars by appointments and promotions committees of HEIs in Nigeria even as more studies are required to expand and validate the established assumptions and criteria.