Reviewerly/exHarmony huggingface dataset:
Cultural Difference or Similarity, Selection of Targets and Post- Acquisition Performance

This paper examines how difference as well as similarity in Individualism-Collectiveness cultural background between the acquirer and target affects the acquirer’s post-acquisition performance during internationalization. Besides examining how distance in individualism will affect acquirer’s post-acquisition performance, two groups will be compared to find out whether the heterogenous types of similarity in Individualism-Collectiveness will affect the post-acquisition performance differently. The first study of the analysis of 681 cross- border deals reveals that a bigger difference in individualism is indeed negatively associated with post-acquisition performance; and this negative association will be tampered if there is a national status difference between the acquirer and the target. The second study of the analysis of 867 cross-border deals tests how similarity in Individualism-Collectiveness influences acquirer's post-acquisition performance. This test further reveals that when the acquirer and the target both come from collectivistic cultures, the post-acquisition performance will be better compared to the situation where both firms come from individualistic nations. These findings enrich the current literature that has focused on the difference of cultural background of acquisition by revealing effects of different types of cultural similarity on acquisition performance, meanwhile offer interesting implications for corporate managers when search for potential acquisition targets.
CPrune: Compiler-Informed Model Pruning for Efficient Target-Aware DNN Execution

Mobile devices run deep learning models for various purposes, such as image classification and speech recognition. Due to the resource constraints of mobile devices, researchers have focused on either making a lightweight deep neural network (DNN) model using model pruning or generating an efficient code using compiler optimization. Surprisingly, we found that the straightforward integration between model compression and compiler auto-tuning often does not produce the most efficient model for a target device. We propose CPrune, a compiler-informed model pruning for efficient target-aware DNN execution to support an application with a required target accuracy. CPrune makes a lightweight DNN model through informed pruning based on the structural information of subgraphs built during the compiler tuning process. Our experimental results show that CPrune increases the DNN execution speed up to 2.73 $$\times $$ compared to the state-of-the-art TVM auto-tune while satisfying the accuracy requirement.
Harnessing Information Communication Technology to Promote Healthcare Access by Women Living in Rural Areas : Opportunities and Challenges

In today’s world, Information and Communication Technology (ICT) is the driving force behind all economic, financial, technological and social developments. It is a tool that has reached and impacted individuals, organizations and nations globally. In the last couple of decades, ICT has revolutionized the medical field in a tremendous way. ICTs have impacted healthcare sector through sharing of public health information, diagnosis and treatment, facilitation of collaboration and cooperation among healthcare workers, remote consultation, effective health research, monitoring health incidences and improving overall efficiency of healthcare facilities. In this paper, desktop exploratory study was conducted to find out how ICT can be harnessed to promote healthcare access by women in rural areas considering associated opportunities and challenges. It looks at uptake of ICT in healthcare in developed countries versus developing nations. It concludes by outlining the opportunities and challenges associated with the application and use of ICTs by women living in rural areas.
The Data Mining Test: An Unexpectedly Effective Tool to Promote Soft and Hard Skills, In Earth Sciences

This article presents a recent experience of the serialization of new educational tools and approaches, which became necessary because of the pandemic, and the need to work online. As it is well known, the use of ‘distance learning’ has had several consequences. It has required everyone, teachers, and students alike, to acquire new digital skills: it has entailed psychological disadvantages, such as social isolation, and didactic-educational ones, such as a lack of transparency in the recognition and certification of skills, knowledge, and abilities, which are difficult to measure behind a screen. But it has also required teachers to renew their methodological approaches and to make the best possible use of the tools offered by the new technologies. In Earth Sciences, as in many other disciplines, the frontal approach is the easiest and traditionally most used, especially in front of a silent and dark screen, where the students on-line are represented just by letters or symbols, but it is certainly the least effective in engaging and exciting students. The endless virtual tools available on the web, films, animations, presentations can partly help the teacher to overcome this obstacle, but they cannot replace educational approaches of active teaching, which allow to develop the students’ interest in this field of knowledge and promote skills. In this research we aimed to build models and paths that use data readily available on the web, such as maps, apps, images, useful for the development of hard skills related to Earth Sciences, but also soft skills, such as critical thinking, problem solving, digital literacy, increasingly required in the world of work. The tool used is the Data Mining Test, a tool that requires commitment and practice in its implementation but is very effective. The research is underway, but the results of the first experiments are proving interesting.
The Accuracy of Magnetic Resonance Imaging in Diagnosing Malignant Breast Lesions

Objective: The present research seeks to examine the diagnostic accuracy of magnetic resonance spectroscopy in the diagnosis of malignant breast lesions using histopathology as the gold standard. Study Design: Cross-sectional Place and Duration: Sadiq Abassi Hospital Bahawalpur. July-21 to Dec-21 Methods: There were 110 females were presented in this study. Patients had with suspicious palpable lesions for malignancy were included. Before any patient data was collected, they signed a permission form acknowledging they understood the risks. The kinetics and morphology of magnetic resonance spectroscopy (MRS) dynamically enhanced pictures acquired with contrast on 1.5 Tesla MRI equipment were evaluated. The choline peak (Cho) permitted by MRS was used to determine a malignancy biomarker.. Single-voxel approach was used to examine MRS' diagnostic performance in breast lesions malignancy. Comparing MRS and biopsy results was done. This version of SPSS 22.0 was used to analyse all the data. Results: Majority of the patients 50 (45.5%) were from age group 41-60years, 35 (31.8%) patients had age &gt; 60 years and 25 (22.7%) were from age group 20-40 years. Frequency of malignant lesion by MRS was found among 92 (83.6%) cases and by histopathological results its frequency was 81 (73.6%). Ductal enhancement and peripheral enhancement were the most common morphology among patients of malignant lesion by MRS. According to MRS findings, 75% specificity,86.7% accuracy, 91%sensitivty, 79% negative predictive value (NPV) and 92.3% positive predictive value were found. Conclusion: As a main imaging tool for the diagnosis of breast lesion malignancy, MRS must be used because of its superior specificity, sensitivity, and accuracy in the characterisation of breast lumps. It has been discovered that MRS is a very specific, sensitive, and reliable diagnostic tool for detecting malignant breast cancers. Keywords: Malignant breast lesion, Histopathology, Magnetic resonance spectroscopy (MRS)
“I’m a Dirt Spoon.” Social Categories and Complaints in Digital Discourse

This paper explores the operation of social categories in the formation and reception of complaints in digital discourse. It adopts membership categorization analysis to examine complaints observed in Korean Internet bulletin board postings. Four postings and their comments are presented as exemplary cases that reflect how categories are utilized in the defense of the poster
JAARBOT

A Chatbot is software to develop interaction between a user/human and a computer/system like human chats. It chats with the client in a discussion to the input of a human and answers the client. It makes the user think it is chatting with a human being, whereas they are chatting with the computer. If it comes to institutions wise, the Chatbot application helps the student and parent to know any information about the college from anywhere with an internet connection and receive fast replies. This Chatbot system reduces the department's work by providing the required information to the student or parent. Also, it reduces the workload to keep on answering all the queries.
THE USE OF AGILE METHODOLOGIES IN MODERN EDUCATION

THE USE OF AGILE METHODOLOGIES IN MODERN EDUCATION Saida Smakova Undergraduate, International Information Technology University, Kazakhstan, Almaty Assem Batyrkhanova Undergraduate, International Information Technology University,
Provision of Mastering of Professional Competences in Agricultural Engineering Specialties

A list of tools for the formation of professional competencies is given. The factors determining the level of their mastering are considered and a model of their formation for engineering areas of training is dev eloped. The ways of mastering professional competencies in the innovative laboratories of the university are described.
Constituent processing in compound and pseudocompound words.

Theories of multimorphemic word recognition generally posit that constituent representations are involved in accessing the whole multimorphemic word. Gagné et al. (2018) found that pseudoconstituents and constituents become available when processing pseudocompound and compound masked primes (e.g., sea is activated in season and seabird). Across four experiments, we examine whether readers access the semantic information of such pseudoconstituents and constituents. Experiments 1 and 2 show that masked pseudocompound and compound primes do not influence lexical decision responses to semantic associates of their pseudoconstituents or constituents (e.g., seabird and season do not influence processing of ocean, an associate of sea). Experiments 3 and 4 show that an associate of the first constituent does not influence processing of the pseudocompound but does facilitate processing of the compound (e.g., ocean facilitates processing of seabird but not of season). While compounds have been found to be sensitive to the activation of their constituents via semantic priming (e.g., El-Bialy et al., 2013; Sandra, 1990), our findings suggest that primarily morphological, rather than semantic, activation of the constituents occurs in a masked priming paradigm. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Various Criteria of Techno- Pedagogy in Teaching- Learning Process

Through this chapter it is aimed to know the various criteria of Techno-pedagogy in teaching -learning process. In this ever evolving world, amendment is that the solely constant. Progress is not possible while not adapting to the dynamical circumstance. As a result of advancements in science and technology there ought a paradigm to shift in teaching -learning method and one to adopt to those changes to be profitable. The impact of technology on education sector is palpable and thought of as a god in disguise because it is aiding in clearing the impediments that prevail within the method of instruction the least bit levels of education. Technology with promote universal access to education render quality education, encourage the teaching fraternity towards their skilled development and the impact of technology on teaching and learning is immeasurable. In teaching -learning process teachers are apply pedagogy in the context of classroom and teachers measure this impact in the achievement of students. So, the multiple skills of teachers are most important in the present day context. In various educational institutions, the technological component is use teacher in the classroom (projectors, slide etc.) So, update of teachers pedagogical skill is most important and its impact to student’s success. Various technological challenges are removing in various contexts. In this perspective due to the rapid change in the field of ICT in teaching -learning process. So, in the present context techno-pedagogical knowledge and skill most important in teaching -learning process.
A Study on Fintech Develop in India

In earlier software development all process is completed and implemented but now this is not a scenario. In modern era changes are frequent to any software product or module which is under development phase, due to market competitions priority of requirement changes Due to the fact that the traditional process models are incompatible with these changes, agile methodology is used instead.. Earlier waterfall model was convenient because of less requirement of features and emergency of the application in the short period of time .This Paper Discusses the comparative Analysis of waterfall model and agile methodologies while agile methodologies are taking over, even the waterfall model is older and time consuming it is still use in many sectors The paper will help other software development process models. Agile method plays important role in the areas of software project management, software schedule management etc. The main aim of the agile is Customer satisfaction as well as faster development with low defect rate. This paper reflects the comparison of the agile processes with waterfall model software development life cycle model. Agile processes aren't always beneficial; they have their own set of downsides. Agile method promotes continuous iteration of development and testing throughout the software developed.
Solving Large‐Scale Linear Systems of Equations by a Quantum Hybrid Algorithm (Ann. Phys. 7/2022)

Quantum Computing A system to solve large-scale linear systems of equations using a quantum processor is described by V. M. Vinokur and co-workers in article number 2200082. The ability to solve linear systems of record size enables simulation of complex networks, fluid dynamics, financial markets, machine learning applications and much more.
APAC2022-Print-Ad-Hybrid-Web (3)

The detection and ranking of pornographic material is a challenging task, especially when it comes to videos, due to factors such as the definition of what is pornographic and its severity level, the volumes of data that need to be processed, as well as temporal ambiguities between the benign and pornographic portions of a video.In this paper we propose a video-based pornographic detection system consisting of a convolutional neural network (CNN) for automatic feature extraction, followed by a recurrent neural network (RNN) in order to exploit the temporal information present in videos. We describe how our system can be used for both video-level labelling as well as for localising pornographic content within videos. Given pornographic video segments, we describe an efficient method for finding sexual objects within the segments, and how the types of detected sexual objects can be used to generate an estimate of the severity (‘harmfulness’) of the pornographic content. This estimate is then utilised for ranking videos based on their severity, a common requirement of law enforcement agencies (LEAs) when it comes to categorising pornographic content.We evaluate our proposed system against a benchmark dataset, achieving results on par with the state of the art, while providing additional benefits such as ranking videos according to their severity level, something which to the best of our knowledge has not been attempted before. We perform further investigations into model generalisability by performing an out-of-distribution (o.o.d.) test, investigate whether our model is making use of shortcut learning, and address the issue of explainability. The results obtained indicate that our model is using strong learning, thus further validating our proposed approach and the results obtained.
Software System Selection for Open University System

Software quality assessment is one of the key factors for the success of universities, so this study focuses on the study of technical quality. Measurement factors apply to universities in information systems, including software quality. The novel model is used to test whether the implementation of e-learning system in higher education institutions will succeed or fail. The scope of this investigation is free and the evaluated universities have open source e-learning systems that measure and evaluate quality according to our proposed software quality model. Educational Information System (AIS), which combines many software quality standards to help system analysts, system developers, and systems. Programmers in their AIS projects. Quality model, six quality characteristics are shown as the minimum requirements for creating a new model. This has been further enhanced by the expansion of the standard approach to measuring the quality of AIS based on a combination of several. Software quality standards used in these educational systems with new features. Using the novel model to test whether e-learning is implemented, the system will succeed or fail in higher education institutions. Our contribution and development will be discussed on this. The new model aims to guide educational institutions that are in the process of creating their e-learning system to evaluate and select the right software. Features that are essential for the success of the entire system. In addition, this paper provides several reviews of current methods used to select AIS components and outlines their disadvantages in terms of our advanced models.
A Low Power Nano AES Security Algorithm For Image Cryptography

Advanced Encryption Standard (AES) is a specification for electronic data encryption. This standard has become one of the most widely used encryption method and has been implemented in both software and hardware. A high-secure symmetric cryptography algorithm, implementation on field-programmable gate array (FPGA). The proposed architecture includes 8-bit data path and five main blocks. We design two specified register banks, Key-Register and State-Register, for storing the plain text, keys, and intermediate data. This project is simulated by Modelsim 6.4 c and synthesized by Xilinx tool.
A Study on the Influence of the Cooking Practice Educational Environment upon the Education Satisfaction and the Career Decision-making Self Efficacy

The purpose of this study is to closely examine whether the cooking practice educational environment has influence upon the education satisfaction and the career decision-making self efficacy targeting the college students majoring in hotel dining cooking. As a result of the analysis, first, the education satisfaction was indicated to be affected by the teaching education competence, the education program and the administrative service, which are sub-factors of the cooking practice educational environment. However, the cooking practice facility did not have a meaningful impact. Second, the career decision-making self efficacy was significantly influenced by the teaching education competence and the cooking practice facility, which are sub-factors of the cooking practice educational environment. The education program and the administrative service appeared not to have an effect. Finally, the education satisfaction with the cooking practice educational environment was verified to have a meaningful influence upon the career decision-making self efficacy.
CONTENT OF LABOR EDUCATION AND TECHNOLOGY TEACHER’S TRAINING AS A REFLECTION OF HUMAN PRODUCTIVE ACTIVITY EXPERIENCE

The article reflects the state of the content of technological education in relation to directions of development, increasing the efficiency and safety of the functioning of technogenic society. It is shown that the training of the younger generation is carried out by various educational branches consisting of academic disciplines. The scope and content of these fields of knowledge and the structure of connections between them determine the level of education at this stage of society’s development. The higher the level of a person’s education, the more fully the surrounding world is reflected in his consciousness, the more deeply he is aware of his place in it, the greater the degree of his responsibility for maintaining harmony in this world, the easier is the integration of a person in society.It is shown that rapid technological development provides humanity with qualitatively new living conditions, increases human capabilities, and accelerates the processes of learning about the surrounding world. On the other hand, the development of technologies often has a detrimental effect on the biosphere and leads to irreversible consequences, forcing us to look for ways of safe interaction between the biosphere and the technosphere.An analysis of the concept of “technology” is presented. It was found that there are dozens of definitions of this concept, but the question of establishing the most significant one, which would correspond to this multi-meaning entity, remains open. It was determined that technology and engineering are not aimed at obtaining knowledge for its own sake, but involve their development and use for practical purposes, they are, first of all, practice based on knowledge.Furthermore, it is proven that the content of this educational field is intended to reflect the existing level of technical and technological culture of society, to show development trends and opportunities for self-determination and self-realization of the individual in the modern technological world.&#x0D; Keywords: technique; technology; “Technology” field of study; technogenic society; technosphere; biosphere; technological education; technological culture.
Detection of Credit Card Fraud Transactions using Machine Learning based Algorithm

The rapid growth in E-Commerce industry has lead to an exponential increase in the use of credit cards for online purchases and consequently they has been surge in the fraud related to it .In recent years, For banks has become very difficult for detecting the fraud in credit card system. Machine learning plays a vital role for detecting the credit card fraud in the transactions. For predicting these transactions banks make use of various machine learning methodologies, past data has been collected and new features are been used for enhancing the predictive power. The performance of fraud detecting in credit card transactions is greatly affected by the sampling approach on data-set, selection of variables and detection techniques used. This paper investigates the performance of SVM, decision tree and random forest for credit card fraud detection. Dataset of credit card transactions is collected from kaggle and it contains a total of 2,84,808 credit card transactions of a European bank data set. It considers fraud transactions as the “positive class” and genuine ones as the “negative class” .The data set is highly imbalanced, it has about 0.172% of fraud transactions and the rest are genuine transactions. The author has been done oversampling to balance the data set, which resulted in 60% of fraud transactions and 40% genuine ones. The three techniques are applied for the dataset and work is implemented in R language. The performance of the techniques is evaluated for different variables based on sensitivity, specificity, accuracy and error rate. The result shows of accuracy for SVM, Decision tree and random forest classifier are 90.0, 94.3, 95.5 respectively. The comparative results show that the Random forest performs better than the SVM and decision tree techniques.