Reviewerly/exHarmony huggingface dataset:
Security Enhancement Through Compiler-Assisted Software Diversity With Deep Reinforcement Learning

Traditional software defenses take corresponding actions after the attacks are discovered. The defenders in this situation are comparatively passive because the attackers may try many different ways to find vulnerability and bugs but the software remains static. This leads to the imbalance between offense and defense. Software diversity alleviates the current threats by implementing a heterogeneous software system. The N-Variant eXecution (NVX) systems, effective and applicable runtime diversifying methods, apply multiple variants to imporove software security. Higher diversity can lead to less vulnerabilities that attacks can exploit. However, runtime diversifying methods such as address randomization and reverse stack can only provide limited diversity to the system. Thus, we enhance the diversity of variants with a compiler-assisted approach. We use a Deep Reinforcement Learning-based algorithm to generate variants, ensuring the high diversity of the system. For different numbers of variants, we show the results of the Deep Q Network algorithm under different parameter settings.
Application of image fusion technology in emergency prevention and control

At present, with the rapid development of science and technology such as computer and electronic information, it also drives the renewal of technology application in emergency prevention and control. Information fusion is a new technology developed to meet this demand. Image fusion technology is an important branch of multi-sensor information fusion. By analyzing the current situation and problems of emergency prevention and control, this paper puts forward the necessity of using image fusion technology, introduces the current situation, levels methods and application scenarios of image fusion technology, and explores the application of image fusion monitoring in emergency prevention and control. It is of great significance for the prevention and control of emergency events and the construction of social security.
Design of the Internet of Things development system based on STM32

In today's advanced technology, students’ hands-on ability has become a focus of every school, such as engineering, agronomy, medicine and other disciplines. The development of the system introduced in this article has greatly increased the joy of learning for college students in related majors, while also focusing on training. In order to improve the practical ability of modern college students and serve more colleges and teachers and students, the development of the Internet of Things system is essential. In the past year, according to the data issued by some colleges and universities every year, there are more excellent graduates and excellent graduation designs and papers in schools that have introduced the Internet of Things development system than when the system was not used before. The overall average has increased by %8, and high-quality employment has increased by %10. With the development and progress of the Internet of Things development system, more and more college teachers and students’ praise shows that the development and design of the Internet of Things development system is very important. This article uses STM32F429 as the core of the Internet of Things development system[1], and measured and tested in a real environment, and repeated the boot test, after comparison and analysis, under the same function, compared with STM32F401 and other series of single-chip microcomputers as the core Embedded system, indoor and outdoor detection of temperature and humidity, and toxic gas detection, vibration test, light sensitivity test, control of stepping motor, this kind of sensor[4] and equipment have higher, more accurate and reliable measurement. As a result, better operability, more stable system, and energy efficiency have been greatly improved.
Impact of Servant Leadership and Organizational Culture on Work Engagement: An Empirical Analysis

The study's goal is to see how servant leadership and corporate culture affect work engagement. While leadership has been proven to have an impact, the effect and procedure underlying work engagement has attracted scant attention. Despite the fact that servant leadership followers are more inclined to be involved, this is especially relevant of servant leadership. We investigate the role organizational culture plays like a potential mediator in the study below, seeking to discover whether servant leadership builds organizational culture that, as a result, enhances work engagement. Overall,we find strong evidence suggesting servant leadership can forecast organizational culture along with the other extensions related to job engagement which include dedication, absorption and vigor, while organizational culture, undermines the effect of servant leadership style. Lastly,all three components of work engagement are positively related to an organization's culture.
Oncotype results compared to standard pathological markers: A five year audit 2015 -2020 NHS Lanarkshire

Aims: Oncotype Dx is a multi-gene test used to help define the prognosis in ER+ve node -ve breast cancer. This audit examines whether there is any further patient or pathological data that might refine the population that should get the oncotype funded.
The Diachronic Evolution of the Adverbization of Te-verb Form in Japanese from Recent to Modern Period

In the process of language evolution, some te-verb forms in Japanese have been converted into adverbial modifiers or complete adverbs for modifying predicates. The conversion from the verb to the adverbial modifier or to the adverb is a gradual process. On the basis of the previous researches, this paper takes「敢えて」,「極めて」,「初めて」,「改めて」,「好んで」and「目立って」as the research objects, and through the investigation of corpus to explore the evolution of te-verb forms to adverbial modifiers or adverbs in diachronic process from recent period to modern one. With the observation of the frequency and semantic changes, the degrees of adverbization of the research objects have been improved or reduced, and the conversion of word classes is a process of dynamic change.
Template based Question Answering System Over Semantic Web

Question Answering system is the most promising way of retrieving data from the available knowledge base to the end-users, to get the appropriate result for their questions. Many Question Answering systems convert the questions into triples which are mapped to the Knowledge base from which answer is derived. However, these triples do not express the semantic representation of the question, due to which the answers cannot be located. To handle this, a template-based approach is proposed which classifies the question types and finds appropriate SPARQL query template for each type including comparatives and superlatives. The SPARQL query built is executed in the DBpedia endpoint and results are obtained. Compared with other factoid question answering systems, the proposed approach has the potential to deal with a large number of question types, including comparatives and superlatives. Also, the experimental evaluations of the system performed on the QALD 8 dataset presents good performance and can help users to find answers to their questions.
Rating consistency is consistently underrated

Content-based and hybrid recommender systems rely on item-tag ratings to make recommendations. An example of an item-tag rating is the degree to which the tag "comedy" applies to the movie "Back to the Future (1985)". Ratings are often generated by human annotators who can be inconsistent with one another. However, many recommender systems take item-tag ratings at face value, assuming them all to be equally valid. In this paper, we investigate the inconsistency of item-tag ratings together with contextual factors that could affect consistency in the movie domain. We conducted semi-structured interviews to identify potential reasons for rating inconsistency. Next, we used these reasons to design a survey, which we ran on Amazon Mechanical Turk. We collected 6,070 ratings from 665 annotators across 142 movies and 80 tags. Our analysis shows that ~45% of ratings are inconsistent with the mode rating for a given movie-tag pair. We found that the single most important factor for rating inconsistency is the annotator's perceived ease of rating, suggesting that annotators are at least tacitly aware of the quality of their own ratings. We also found that subjective tags (e.g. "funny", "boring") are more inconsistent than objective tags (e.g. "robots", "aliens"), and are associated with lower tag familiarity and lower perceived ease of rating.
Cryptocurrencies in the COVID-19 era

The purpose of the article is to describe the state of the financial market during and after the COVID-19 pandemic. The financial environment is facing new questions about the future, one of which concerns the role played by cryptocurrencies in the coming years. In recent years the cryptocurrency market has been experiencing spectacular growth, with more than 5,500 cryptocurrencies now in existence worldwide. They can either be used as safe haven currencies that provide protection against market volatility or as a payment system with the prospect of consolidation. Whatever the case may be, the pandemic circumstances favour the development of these digital assets. The crisis generated by the pandemic has also affected the value of bitcoin, which has been quite volatile. While it seems to be recovering, the near future is uncertain. The uncertainty brought about by the coronavirus health crisis has caused a general collapse in the stock markets. In this context, the authors review the behaviour of bitcoin, with its dips and recoveries, which can occur in a matter of a few hours. The first months of national lockdowns were mainly marked by social issues. When social distancing has become the norm, cryptocurrencies can play a bigger role than they did previously, driving the evolution of money away from cash in the direction of cashless society.
Breast conserving surgery with wire localisation: Bangladesh experience

Background: With the introduction of breast screening, high quality digital mammography and increased public awareness there has been seen an increase diagnosis of non-palpable, smaller breast lesions including cancers. Accurate localisation of small, non palpable breast lesion is mandatory for good surgical management. The first author has pioneered the introduction of wire localisation, hydrogel marker insertion technology in Bangladesh and first three case were done by him at BSMMU live surgery workshop in March 2018.
Utilizations of IoT In Education for Visual Impairment Students

IoT intelligence can help ease daily tasks with the use of intelligent environments where it combines human interaction and IoT technology. The IoT has a great context-sensitive delivery feature in supporting and focusing on the use of technology in increasingly sophisticated education. Being born with a disability or getting a disability impairs daily tasks and provides additional challenges in continuing education. This challenge is highly dependent on the type of disability which may be either a physical disability or a mental disability. People with Disabilities are people who have physical and/or mental disorders, which can interfere with or are obstacles and barriers for them to perform activities normally. Such disabilities can come physically, mentally as well as both. Disorders are problems with body function or structure, activity restrictions are difficulties faced by individuals in performing tasks or actions, while barriers to engagement are problems experienced by individuals in engaging in life situations. high to pursue education in various domains. To address this, assistive devices that integrate IoT technology are growing rapidly especially for students with visual impairments. After that, the exploration of IoT applications and assistive devices in education continues. The advancement of IoT is used in various ways to develop current technologies in many areas of technology. Efforts to improve the well-being of learning and teaching for the disabled based on the use of tools to help the disabled are very useful. Many assisted technologies available in the market to accommodate each of these groups have the same opportunity in all aspects of life and livelihood of the disabled, especially students in the market at a very cheap price and easily available. In addition, it can also attract students with disabilities to carry out daily work activities and smooth learning as possible. For this reason, IoT-assisted technology should be able to help visually impaired and blind students to continue their education comfortably.
Chatbot Analysis

Chatbot is broadly popular now-a-days and easily spread speed as an application of computer communiqué. Some programs respond sharply like human. This type of program is called a Chatbot. For this purpose, many open source platforms are available. Artificial Intelligence Markup Language (AIML) is derived from Extensible Markup Language (XML) which is used to build up a conversational agent (chatbot) artificially this paper address the design and execution of a Chatbot system. We will also study another application where Chabot’s could be helpful and techniques used while designing a Chatbot.
Face recognition based attendancemanagement system

In this modern era, the technology plays an important role . Face recognition technology is one of the most widely used . It can be used for either in security, authentication, identification, like in phones also this technology is used very widely to unlock the phone. Aside from having low accuracy compared to the detection of the iris and the recognition of fingerprints, it is widely used due to its transthoracic and transthoracic procedure. In addition, this technology is also used in various places like school,colleges,hospitals and many other places. This technology is generally used for schools and colleges to provide the facility to the teacher like to decrease the burden of the teachers because it is very time consuming to take the attendance with the help of the pen paper based so it is less time consuming. And there may be opportunities for the presence of a representative. Thus, the demand for this program is growing. The program consists of sections consisting of archival construction, facial recognition, facial recognition, attendance development. The software is created by pictures of students in the classroom. Face detection software are performed using the Haar-Cascade algorithm respectively.
Automatic Generation of Minutes of Meetings

This paper describes the process for automatic generation of minutes of meetings using Machine Learning algorithms and Natural Language Processing techniques. Minutes of meetings are a record which are used to keep official summaries of all meetings conducted within a company or organization. Automatic generation of minutes of meeting is a challenging issue and has gathered a huge amount of interest over the last few years due to its applications. Initially, we study previous research papers to understand existing techniques used for the purpose. Techniques such as AMBOC Model, BART Summarizer, HMNet Model, MSCG are employed for detecting useful and informative action items from audio files. Then we explore Machine Learning models such as SVM, HMM which are clubbed with the majority of methods for classification and summarization of the words given by above mentioned models to generate an informative summary for the user.
Learning a Language using Grammar Translation Method

This paper presents the methods used for learning a language. Here, we specifically talk about Grammar Translation Method which is a long-established way of learning a language. The paper tries to analyze the effectiveness of this method of learning and to evaluate its conduciveness for teaching. It further shows us “how a student actually learns a language using Grammar-Translation method”. The paper tries to evaluate to what extent this method of learning the language is adequate for the learners. This paper attempts to discuss the role of a teacher and other factors like syllabus, teaching environment, study materials etc. in the learning process.
PENERAPAN METODE EKSPONENTIAL SMOOTHING DALAM MEMPREDIKSI JUMLAH PESERTA DIDIK BARU DI SMA FAVORIT KOTA PAYAKUMBUH

Forecasting is a technique for estimating a value on a particular object in the future by paying attention to past data. This forecasting uses the Exponential Smoothing models because the data used is in accordance with the model. This study aims to predict the number of students in favorite high schools in Payakumbuh based on data obtained from 2014 until 2021 which is grouped into science and social studies classes. Forecasting is done using a Single Exponential Smoothing and Double Exponential models. MAPE results show that the Double Exponential Smoothing model is better at predicting the number of new students than Single Exponential Smoothing. Keywords: Double exponential smoothing, forecasting, single exponential smoothingMSC2020: 62M10
Restoration of Ancient Document Images Using Phase Based Binarization

The main defects present in historical documents are darkness, non-uniform clarification, bleed-through and faded characters. To remove these defects binarization method is used. In this paper a phase based binarization method is studied in which phase of ancient document images is preserved. This method is derived in to three steps: preprocessing, main binarization and post processing. In preprocessing phase preserved denoised image is derived. In main binarization two phase feature maps are derived are maximum moment of phase congruency covariance and a locally weighted mean phase angle. At last in post processing Gaussian and median filter is use for enhancement of image. It is also improve the performance of binarization methodologies.
SECURE INFORMATION EXCHANGE WITHOUT PRIOR KEY DISTRIBUTION VIA SINGLE-PHOTON HYPERSTATES

Methods for two distant parties to exchange their secret messages usingsingle photons are considered. There existed several such methods but theyare either insecure or face with information leakage\ problem. Recently, Ye \textit{et al.} [Quantum Inf. Process. 20 (2021) 209] have reported a methodusing single photons in both polarization and spatial degrees of freedomthat is both efficient and resistant from information leakage. However, thismethod is not so feasible as it has specific limitations, namely, itrequires availability of quantum memory and high classical communicationcost. We propose in this paper a new method to overcome the above-saidlimitations. Our method is also efficient because we also use single photonsin two degrees of freedom. However, the encoding operation in our method ismodified so that no quantum memory is demanded at all and the execution ofour method is simpler compared to the method of Ye \textit{et al.}.Moreover, the cost of classical communication in our method is 50\% cheaperthan that in the method of Ye \textit{et al.} Therefore, our method provesto be feasible, simple and economical that could be realized by means ofcurrent technologies.
TARGET TRACKING IN COMPLEX SCENES BASED ON COMPUTER VISION

ABSTRACT Objective: Use the deep learning network model to identify key content in videos. Methodology: After reviewing the literature on computer vision, the feature extraction of the target video from the network using deep learning with the time-series data enhancement method was performed. The preprocessing method for data augmentation and Spatio-temporal feature extraction on the video based on LI3D network was explained. Accuracy rate, precision, and recall were used as indices. Results: The three indicators increased from 0.85, 0.88, and 0.84 to 0.89, 0.90, and 0.88, respectively. This shows that the LI3D network model maintains a high recall rate accompanied by high accuracy after data augmentation. The accuracy and loss function curves of the training phase show that the accuracy of the network is greatly improved compared to I3D. Conclusion: The experiment proves that the LI3D model is more stable and has faster convergence. By comparing the accuracy curve and loss function curve during LI3D, LI3D-LSTM, and LI3D-BiLSTM training, it is found that the LI3D-BiLSTM model converges faster. Level of evidence II; Therapeutic studies - investigation of treatment results.
DEVELOPMENT OF MOBILE APPLICATION FOR SALARY CALCULATION

This article analyzes existing mobile applications for calculation of wages; also we considered main stages of creation mobile applications. Calculation method for determining of the amount of wages in Kyrgyz Republic has been determined. Android operating system, Java programming language and Android Studio integrated development environment are briefly considered in it. Start box for entering applications has been developed and input activities’ process and employee data output determine salary are shown.
The effect of self-control following face-to-face and non-face-to-face elementary school physical education classes on satisfaction with physical education classes

The purpose of this study is to verify how self-control according to non-face-to-face and face-to-face physical education classes due to the COVID-19 situation affects the satisfaction of physical education classes. For this purpose, a questionnaire survey was conducted on face-to-face and non-face-to-face physical education classes for 350 elementary school students in Seoul. Using AMOS 21.0, the construct validity of the questionnaire was verified, and hierarchical regression analysis was performed using SPSS18.0. The result is as follows. First, in the case of students participating in face-to-face physical education class, the satisfaction level of the physical education class was significantly higher in each sub-factor than the students participating in non-face-to-face physical education class. Second, in all factors of physical education class satisfaction, long-term self-control had a high level of influence on physical education class satisfaction, and this effect was stronger in the non-face-to-face class participation student group. Third, in the case of class evaluation satisfaction, short-term self-control showed a negative relationship at a significant level only for students participating in non-face-to-face classes. This study is meaningful in exploring the possibility of increasing the satisfaction of non-face-to-face physical education classes that can be used in various ways in the future by examining the relationship between satisfaction and self-control of non-face-to-face and face-to-face physical education classes.
Symposium: Cognitive Science Education

As is well known, teaching cognitive science presents some special challenges, whether to undergraduates or to graduate students. In this symposium, we aim to explore some of the problems that teaching cognitive science presents in the class- or seminar room and identify some of the special opportunities.
Incremental Interpretation and Lexicalized Grammar

The increasing lexicalization of syntactic theories poses new difficulties for incremental models of language processing. In this paper, we describe an incremental interpreter that makes use of knowledge on categories to keep the syntactic structure always connected. This, in turn, guarantees a fine-grained syntax-semantics interaction. The paper introduces the general problem of formalizing the notion of incremental interpretation, and analyzes the current approaches in the cognitive literature.