Reviewerly/exHarmony huggingface dataset:
Using Feature Extraction and Classification Methods of Movie Opinions Predication

Film rankings and analysis at sites like IMDb (Internet Movie Database) square measure ordinarily employed by picture show goers to make your mind up that movie to look at or obtain next. Currently, picture show goers base their choices on that movie to look at by staring at the ratings of films in addition as reading a number of the reviews at IMDB. Sentiment analysis could be a different field of different opinion where the methods of analysis are targeted on feature extraction and selection technique of emotions and opinions of the individual’s audience towards selected methods from semi-structured, structured or unstructured matter information. This paper, we focus on our techniques of sentimental analysis on IMDB picture show review information. To survey the sentimental words method to classify the polarity of the picture show review on a scale of highly dislikes highly liking and performing different extraction feature and positioning of reviews. It uses these options to train our multilable classifier to classify the picture show review into its correctable.
Preface

Abstract Simposium Kebangsaan Sains Matematik ke-28 (SKSM28) 28-29 July 2021, Virtual Platform (Microsoft Teams) Simposium Kebangsaan Sains Matematik is an annual program of Persatuan Sains Matematik Malaysia (PERSAMA) in cooperation with the local university in Malaysia. In its 28 th edition, PERSAMA has invited Centre for Mathematical Sciences, Universiti Malaysia Pahang to be the host of the event. The symposium brings together local and international intellectuals in Science and Mathematics from within and outside the country to share their recent research output. The topics of the symposium including, but not limited to, Pure Mathematics, Applied Mathematics, Computational Mathematics, Statistics &amp; Applied Statistics, Operational Research, Mathematics Education and Data Science. The SKSM28 with the theme Sains Matematik Wahana Pencetus Inovasi Sejagat is held virtually due to the travelling restriction imposed. Nevertheless, the event successfully attracts more than 200 submissions. This Proceedings issue compiles the fullpaper submissions that were submitted by the authors and rigorously reviewed by the reviewers who are expert in their fields. Despite the pandemic outbreak, SKSM28 is an overwhelming success, attracting the delegates, speakers and sponsors from academics and industries, as well as providing a great intellectual and social interaction for the participants. Without their support, the conference would not have been the success that it is. We trust that all the participants found their involvement in the symposium both valuable and rewarding. Once again, we would like to convey our deepest appreciation for all contributions and wish you success in the years ahead. List of Editors, Conference/Sponsor Logo, Organising Committee, Scientific Committee, Keynote Speakers, and this titles are available in this pdf
|Vol. 6| No. 2|Year 2019

Edukasi: Jurnal Pendidikan dan Pengajaran provides a vital forum for exchanging ideas in order to enrich the theories and practices of English education in Indonesia and across the globe. The journal focuses, but not limited to, on the following topics: English language teaching, language teaching and learning, language teaching methodologies, pedagogical techniques, teaching and curricular practices, curriculum development and teaching methods,program, syllabus, and materials design, second and foreign language teaching and learning, language education, teacher education and professional development, teacher training, crosscultural studies, bilingual and multilingual education, translation, language teaching for specific purposes, new technologies in language teaching, and testing and evaluation. It provides an academic platform for teachers, lecturers, and researchers to contribute innovative work in the field.
A Procedure to Prevent Confidential Information Leakage of Government Organizations in Bangladesh using Isakmp Cryptographic Technique

To ensure security for the transmission of confidential information, Cryptographic algorithms play an important role in providing security against malicious attacks. Confidential information is exchanged among different organizations of the government. If the necessary security is not involved there, the information will be leaked due to un-trusted transmission, unattended nature and get access easily which can cause a disaster in the government system. In this research, my centre of attention is to prevent confidential information leakage in government organization using ISAKMP cryptographic technique.
The analysis of the conditions influencing the development efficiency of the project managing in education

Today, the role of education is increasing in order to preserve and develop the advantages of the nation and the country's social and economic development. The strategic goals of education development require new implementation tools. The project activity plays a special role in this process; however, it is often formal and chaotic. There is a need to create effective project management systems in education and to improve the management and teaching staff competencies. In order to achieve this, it is necessary to understand whether the conditions for training systems formation for project management personnel are created. The study made it possible to determine the key constraining factor for the effective implementation of project management in education - the lack of unifed training methodology basics, and also clear bias of training programs towards one of its «project» component. The study uses the methods of theoretical research, these are: comparison, synthesis, methods of grouping and classifcation. We also used the method of data collection through the analysis of regional institutions of education development websites information. All in all there were involved 24 higher educational establishments: 3 random institutions from each federal district of Russian Federation.
Introducing Bayes

Summary Some situations are presented with perplexing properties, which become clearer by looking at contingency tables. This in turn leads to problems that can be solved using conditional frequencies and thus leading to the Bayes formula with natural frequencies or probabilities.
WEIGHTED STRUCTURAL SUPPORT VECTOR MACHINE

In binary classification problems, two classes of data seem to be different from each other. It is expected to be more complicated due to the clusters in each class also tend to be different. Traditional algorithms as Support Vector Machine (SVM) or Twin Support Vector Machine (TWSVM) cannot sufficiently exploit structural information with cluster granularity of the data, cause limitation on the capability of simulation of data trends. Structural Twin Support Vector Machine (S-TWSVM) sufficiently exploits structural information with cluster granularity for learning a represented hyperplane. Therefore, the capability of S-TWSVM’s data simulation is better than that of TWSVM. However, for the datasets where each class consists of clusters of different trends, the S-TWSVM’s data simulation capability seems restricted. Besides, the training time of S-TWSVM has not been improved compared to TWSVM. This paper proposes a new Weighted Structural - Support Vector Machine (called WS-SVM) for binary classification problems with a class-vs-clusters strategy. Experimental results show that WS-SVM could describe the tendency of the distribution of cluster information. Furthermore, both the theory and experiment show that the training time of the WS-SVM for classification problem has significantly improved compared to S-TWSVM.
Research on Privacy Preservation of Big Data Challenges and Real Time Applications

Our examination work is the most slanting since it relates to the security issues which increase, well ordered in view of the casual association inclines in society. In this paper we address the issue of uncovering an individual's information; the philosophy depends for the most part on the K-anonymity with the possibility of unimportant theory, which gets the property of the release strategy not to ravage the data more than anticipated to achieve K-lack of definition. We talk about the colossal data in detail how it is useful to guarantee an immense volume of information without change the arrangement of one of a kind data. Data stored in different forms is anonymise efficiently without affecting the integrity if data by using K-Anonymity and Artificial Bee Colony algorithm respectively. We similarly give base on security and insurance strategies and to avoid the interference. We use the phony bumble bee settlement (ABC) count to propel the tremendous enlightening accumulation. We exhibit the result in graphically the sum we improve the insurance from the as of proposed system. Here both K-Anonymity and ABC Algorithm is used (mixed) which never took care by executing parallel.
Giant pandas protected by face ID

A facial recognition app that can tell one giant panda from another is being used by animal conservation experts in China.
Time of Development and Fitness Analysis of Modified COCOMOII Model for Software Projects

In the management of software projects, software cost estimate is very important. The absence of precise and premature estimates is a significant source of the inability of many software initiatives. Nevertheless, it remains a challenge for the software industry to correctly estimate the time and the cost of development. It is used to predict how much effort and time the project needs. The precision of the technology proposal usually depends on the estimated time and the strength standard of the template. In this research analysis the time of development and model fitness are analyzed as a major contribution. The optimized coefficient values for A, B, C &amp; D is used to estimate the time of development and model fitness. This experimental analysis proved that the time of development and model fitness analysis shows the great significance in the estimation and their influence in software cost estimation.
Introduction

Introduction of our concepts of Passive Scene Recognition and Active Scene Recognition as well as of our research statements and contributions.
INTEGRATING MEDIA DIDACTIC COMPETENCES IN PSYCHOLOGY COURSES OF TEACHER EDUCATION

Internationally, ICT have become an integral part of school curricula in recent years.As a consequence, teacher education has the aim of imparting the necessary knowledge for the effective use of ICT.The TPACK framework is a frequently used theoretical basis to achieve this goal.In our study we investigate to what extent TPACK is promoted in a psychology course and how TPACK development correlates with other aspects of professional teachers.Results show that educational psychology courses can promote TPACK and that aspects of motivation or comprehension of constructivist learning settings should be considered in the conceptualization of courses with the aim to promote TPACK.
Towards Association Rule-based Item Selection Strategy in Computerized Adaptive Testing

One of the most important stages of Computerized Adaptive Testing is the selection of items, in which various methods are used, which have certain weaknesses at the time of implementation. Therefore, in this paper, it is proposed the integration of Association Rule Mining as an item selection criterion in a CAT system. We present the analysis of association rule mining algorithms such as Apriori, FP-Growth, PredictiveApriori and Tertius into two data set with the purpose of knowing the advantages and disadvantages of each algorithm and choose the most suitable. We compare the algorithms considering number of rules discovered, average support and confidence, and velocity. According to the experiments, Apriori found rules with greater confidence, support, in less time.
Performance Estimation of 111kWp Grid Interactive Solar PV Power Plant at Integral University

Solar Photovoltaic (SPV) is a novel technology to harvest solar energy as and when we talk about replacing the conventional grid electricity. The degree of development of a country is measured by the amount of energy used by humans. Energy demand is increasing due to population, urbanization and industrialization. As a result conventional electricity needs to be replaced with non conventional energy resources so as to save the environment from pollution due to increased number of unwanted gases and dust particles in the air. Harmful gases like COx and SO2 in the environment are affecting the Air Quality Index (AQI) and making it difficult for humans to breathe. Solar Energy is a clean and green solution to improve the AQI of the earth. In this research we study and analyze the performance of a grid interactive SPV plant installed at Academic Block-II, Integral University. In this regard, we measure the performance ratio for 4 (four) months. The effect of shading on the PV panel is reviewed due to deposition of dust particles and bird feces.
An Accuracy of Attack Detection using Attack Recognition Technique in Multi-Factor Authentication Scheme

One popular scheme used for authentication security is the implementation of multi-factor authentication (MFA). There have been several researches that discusses on multi-factor authentication scheme but most of these research do not entirely protect data against all types of attacks. Furthermore, most current research only focuses on improving the security part of authentication while neglecting other important parts such as the systems accuracy. Accuracy is based on how perfect is the system able to identify a genuine user or an intruder. Current multifactor authentication schemes were simply not designed to have security and accuracy as their focus. Accuracy can be measured as the success rate on tasks that requires a certain degree. For instance, the number of users who is successfully logging into the system using any technique provides a measure of accuracy. Usually, accuracy demands of users are impacted by other demands such as recall of required information, environmental, or other factors. In authentication, the accuracy factor was identified through the device pairing studies. In many cases in the authentication system requires users to enter a password or biometric traits with 100 percent accuracy for comparing it. Nevertheless, this research analyzes the level of accuracy based on the biometric accuracy of authentication. In this paper will explain the evaluation process on the accuracy level of the proposed authentication to get a highly accurate performance, which is based on FAR (false acceptance rate) and FRR (false rejection rate). Result from the experiment shows that the accuracy of proposed scheme is better than the accuracy of other previous schemes. This is even after additional security features has been added to the scheme.
Completion of flood defences enables James Walker to expand further

In the UK, James Walker – which supplies a range of high-performance fluid sealing products – is benefiting from an investment of £2.6 million by Cumbria Local Enterprise Partnership to protect its premises from flooding.
Formalization in Digital Forensic Triage for Identification of Malicious IoT Devices

Considering the large number of devices connected to the Internet of Things(IoT), identifying malicious devices for the purpose of “search &amp; seizure” remainsa critical issue for digital investigators. Consequently, the need for techniques that automatically identify malicious devices can speed up the process of digital investigation. However, few conceptual approaches were proposed to identify malicious devices during IoT forensic investigation. To overcome that, a formal approach is proposed to automatically triage and fingerprint IoT Malicious devices with their respective states. It is expected that with the proposed formal approach, investigators can simply identify malicious devices, their states as well as determine the scope of investigation.
Efficient Technique for word identification and recognition in Telugu Documents

Telugu language is one of the most spoken Indian languages throughout the world. Since it has an old heritage, so Telugu literature and newspaper publications can be scanned to identify individual words. Identification of Telugu word images poses serious problems owing to its complex structure and larger set of individual characters. This paper aims to develop a novel methodology to achieve the same using SIFT (Scale Invariant Feature Transform) features of telugu words and classifying these features using BoVW (bag of visual words). The features are clustered to create a dictionary using k-means clustering. These words are used to create a visual codebook of the word images and the classification is achieved through SVM (Support Vector Machine).
Portion of Heterogeneous Resources of an IoT Gadget to Flexible Services

Internet of Things (IoT) gadgets can be set up with exquisite heterogeneous framework interfaces. An overwhelmingly huge share of companies can also call for a couple or those interfaces' open belongings. as a result, we gift an correct numerical arrangement of consigning agencies to interfaces with heterogeneous resources in any event one rounds. for affordable version sizes, the displayed definition produces ideal publications of motion for this computationally tough hassle. We display the NP-Completeness of the issue and make figurings to appraise the proper reaction for extraordinary model sizes. the principle figuring allocates the most citing business enterprise necessities to start with, brooding about the everyday charge of interfaces assets. The subsequent one unearths out the bringing up useful aid shares and designates the most mentioning of them first through deciding on erratically amongst as alternative mentioning offers. Finally, we deliver propagation comes about giving facts into companies component completed particular interfaces for the 2 times.
Large-Scale Optical Neural-Network Accelerators based on Coherent Detection

We present a coherent optical neural-network accelerator based on homodyne detection that is scalable to large (N &gt; 1000) networks, and analyze the fundamental quantum limits to its energy efficiency.
AWN-similarity: Towards developing free open-source frameworks for measuring Arabic semantic similarity under Windows / Linux operating systems

Arabic is a highly systematic language where its words exhibit elegant and rigorous logic.The field of Arabic word semantic similarity becomes more challenging due to its higher complexity and subtlety.This research is concerned with investigating the development of free open-source frameworks containing packages to calculate the semantic similarity between two Arabic words or concepts.These packages are known as AWN-ConceptSimilarity and AWN-WordSimilarity.The developed packages implement seven semantic similarity algorithms.One of these algorithms was proposed for Arabic and the rest were proposed for English where successfully adapted to Arabic using an Arabic lexical database, Arabic wordnet.The functionality of the developed packages is validated using two-word similarity benchmarks datasets previously produced for Arabic.The results of the validation process indicate that the developed frameworks represent an important contribution to the Arabic semantic similarity field.Moreover, the developed packages are reliable to use and embed them with Arabic researchers' projects for improving or comparing their methodologies.
Provisional Research On Ensemble Learning Techniques For Card Fraud Detection

Machine learning have revolutionized fraud detection in various domains like telecommunication and e-commerce. Global statistics shows how billions of dollars are lost because of card frauds every year and millions of people falling the victims. Fraud detection systems used for credit card fraud detection 2 decades ago are still being used because of the trust and stability they have provided for so long. With a number of academic research being done in fraud detection their effect on the financial industry has been minimum. Even with high prediction accuracy using machine learning approaches like deep learning and stack ensemble most of these research gets directly rejected by the industry. Our research objective is to highlight the reason of rejectection which are mostly ignored by the researchers and there adverse effect on the results
Enabling Multi-Processors and Expert Systems with Yama

Recent advances in encrypted information and pseudorandom communication do not necessarily obviate the need for semaphores [2]. In fact, few analysts would disagree with the construction of context-free grammar. YAMA, our new solution for the emulation of virtual machines, is the solution to all of these obstacles.
Conclusion

Human-centric visual pattern recognition has emerged as one of the most interesting areas of applied research. This is evident from the rising number of publications in this area over the last decade. Perhaps the most prominent area of application is computer vision, where biometric recognition occupies a central part. The need for reliable, accurate, fully automated, and robust biometric recognition systems has motivated intense research in this area. Despite significant progresses being made, the perfect system remains elusive, and research continues on several fronts, the most notable being the construction of highly efficient features for recognition or classification. As Chap. 1 reveals, there are a plethora of features being used for representation of visual patterns.
The Evolution of Computing Education and Paths of Realization in China

That the rapid development of engineering science in the fields of artificial intelligence, internet of things, and big data marks the human society entering into the intelligent stage, which increases the awareness of computing skills cultivations for engineers and technicians.Yet the path of the realization of computing education is not generally defined in China.Within this context, this study intends to firstly list the key nodes and landmark events of Chinese computing education by literature review technique, and summarize its historical context and anticipate the trends.Secondly, using structured case study method, the study selects and analyses four typical cases conducted within Chinese computing education system, and subsequently extracts two paths named integrated path, and specialized path for sustainable development of computing education.Different characteristics of computing education models have been outlined and summarized as four typical paths which are underlying computing education.The concept of computing education is consequently refined and suggestions are put forward for various hierarchies like government, university, and industry, to effectively improve the quality of talent cultivation in computing education in China.
Offshore Software Testing in the Automotive Industry

This paper presents a mixed-method study performed in the software department of an automotive supplier operating in India as an offshore service provider to a German company. The research focuses on the social dimension and human aspects involved in software testing in an intercultural setting. Qualitative and quantitative analyses of testers' perception regarding their daily activities and challenges were conducted. External and internal factors posing recurrent problems for testers were identified. Among the external were late inputs (documentation and software) and lack of recognition on the contribution of testing by other teams. A key internal factor was the view testers themselves hold about testing: boring when describing manual tests and interesting for the automated ones. Some of the testers feel they are not recognized by other teams and are not entirely satisfied with their job. Maintaining motivation over time was found to be a fundamental problem for testers.