Reviewerly/exHarmony huggingface dataset:
Cyber-Crimes and Cyber Laws of Pakistan: An Overview

Communications have become the most essential and quite an easy as well as fast because of technology advancement. Developing states are also getting the same blessings of computer networks and internet like the developed nations of the world. Besides, such the blessings and curses take place on account of communications in the modern technology. Cyberspace - is the medium of communication on computer networking that is not safe. Criminals use such the technology to commit crimes on cyberspace. Meanwhile the sensitive data and information are hacked to injure the person, organization, society or even a state. These (cybercrimes) and criminal may be prevented by making the sufficient laws in a country. The principle aim of this study is to discuss the cybercrimes and examine the cyber laws in Pakistan. For this purpose, there are three parts of this paper. The first part addresses the cyber-crimes explicitly in Pakistan. The second part is dedicated to the legal framework of cyber laws in the country. While the last but not least part talks about the cyber security strategy of Pakistan.
Patentability and PHOSITA in the AI Era—A Japanese Perspective

Abstract Although it may not be clear whether AI may generate the invention autonomously without human intervention, recent development of AI produces inventions of AI technologies such as machine learning (deep learning). Inventors also have begun to use AI as a tool to help them create inventions. These AI-assisted inventions raise the urgent and practical issues of patentability such as patentable subject matter (patent eligibility), disclosure requirements, and inventive step (non-obviousness). The Japanese Patent Office (JPO) updated the Examination Handbook to address some of the issues. For instance, they discussed to what extent inventors should disclose in patent applications because AI as a black box does not explain how the problems are solved. However, the JPO did not pay much attention to the possibilities that not only inventors but also a person having ordinary skills in the art (PHOSITA) might use AI and PHOSITA with the aid of AI could create the inventions more easily, thereby raising the level of inventive step. This chapter critically reviews the JPO’s updated Handbook and discusses whether and how we can take into account the use of AI by PHOSITA in examining inventive step.
Need Analysis of Text for Translation Material in Universitas Negeri Padang

Globalization, industrialization, technology and social media have affected the progress of translation studies from different sides.The present situation makes the need for translation is increasing day by day and the materials to be translated are growing more and more numerous.This research explores the needs of translations' materials related text types in bachelor degree at Universitas Negeri Padang that focused to the compatibility of the translation materials to the translation market.The questionnaires were used because the instrument and therefore the data were analyzed by using Likert Scale.Then, instructors, professionals who are involved within the translation agency were interviewed.To do so, the researcher designs this study as a descriptive research.Therefore, the results show that there are 15 lacks of text types in translation course at Universitas Negeri Padang.additionally, the purpose of departure during this study was that translations' materials related text types and therefore the translation market as two parties to translation service provision should be in close interaction so as to enhance the standard of translation class in higher-education institutions and therefore the quality of translation done on the market.The findings of this research are expected to provide valuable information for curriculum designers in developing learning materials focus on translation subject with the materials are related to the students' need in the translation market.
THE EFFECT OF THE NUMBER OF HIDDEN LAYERS IN THE BACKPROPAGATION IN CASE STUDY WEATHER CLASSIFICATION

In this modern era, there are many algorithms that can be used to classify the weather, one of this algorithms is Backpropagation. Using Backpropagation, this research were using temperature, pressure, humidity, wind speed, rain and clouds as input parameters. And the output are clear, clouds and rain. Backpropagation consists of learning process and testing process. The learning process is to get optimal weight and testing process is to test the classification using the optimal weight from learning process. Data that was used in this research are 1600 data (80%) for learning process and 400 data (20%) for testing process. This research using Backpropagation with 1, 2 and 3 hidden layer to examine the accuracy result of weather classification. As a result, there is no significant changes of percentage accuracy on Backpropagation with 1, 2 and 3 hidden layers. But, the more number of hidden layer it used, the more epoch it requires.
Reversible Data Hiding based on Two-dimensional Histogram Shifting

This paper presents a two-dimensional histogram shifting technique for reversible data hiding algorithm. In order to avoid the distortion drift caused by hiding data into stereo H.264 video, we choose arbitrary embeddable blocks from 4×4 quantized discrete cosine transform luminance blocks which will not affect their adjacent blocks. Two coefficients in each embeddable block are chosen as a hiding coefficient pair. The selected coefficient pairs are classified into different sets on the basis of their values. Data could be hidden according to the set which the value of the coefficient pair belongs to. When the value of one coefficient may be changed by adding or subtracting 1, two data bits could be hidden by using the proposed method, whereas only one data bit could be embedded by employing the conventional histogram shifting. Experiments show that this two-dimensional histogram shifting method can be used to improve the hiding performance.
Students‘ attitudes in the perception of broadcast advertising meanings

The aim of the research presented in the paper is the empirical study of the semantic attitudes and life meanings of students in the perception of advertising posters. Advertising impact is viewed as a process of broadcasting the meanings concentrated in advertising posters. The study sample consisted of 80 students from two universities (Rostov-on-Don, Russia). To determine the severity of life meanings, the method of life meanings was used by V.Yu. Kotlyakov (V.Yu. Kotlyakov, 2003), the method of expert assessments was used to study advertising posters. The results were processed using the methods of mathematical statistics: descriptive statistics were used; as well as nonparametric tests for comparing several independent samples, the Kruskal-Wallis H-test, for studying the relationships between the scales of V.Yu. Kotlyakov and the assessment of advertising posters by the respondents used the Spearmans rank correlation coefficient. It was shown that in the process of broadcasting meanings in advertising posters, students semantic attitudes are actualized. The sample of students showed a tendency to evaluate advertising posters in accordance with the dominant meanings of life. It is shown that there is a relationship between the dominant life meanings of students and the ratings of advertising posters.
A Comprehensive Analysis On Efficient Multimedia Storage Mechanism In Public Cloud Environment With Secured Access

Dynamic on-demand service has become the crucial part in cloud computing according to the user’s requirements. Cloud storage is clearly the top choice for archiving media assets, by choosing the public cloud for active, deep archive needs. Video on demand, media distribution system in cloud allowing users to access video, facilitating immediate download and view of data without traditional video playback devices. On demand service of video requires infrastructure resources to handle large load fluctuations. Major challenges of video demand services are delays in simultaneous video uploading, processing, accessing and traffic caused by exhaust services. Also, there are concerns over the security of assets stored in a public cloud remains. In this paper, an ample analysis is presented on file storage encompassing fragmentation, compression, encryption security concerns in cloud storage and access. The limitations in the existing is also provided and hence outlined the research direction towards an efficient storage mechanism with a secured access providing a reliable media data transmission between data owner and users in public cloud environment.
Evaluating Quality-of-Service in Blockchains Using Modelling and Simulation Tools

A Blockchain is a distributed, decentralized and ordered list of special data structures called as blocks, where each block is connected to its previous block by a special pointer called as hash pointer, resulting in an append only system which only grows in size with time.In designing and implementing Blockchain driven systems many decisions about configuration parameters need to be made in advance.However investigation and experimentation on real systems is not feasible.Blockchain simulators help in deciding about best configuration parameters for design and development of Blockchain based solutions before actually building the real solution.Quality of service is an important aspect in any distributed system, so is the case with Blockchain driven systems.Security, Auditability, Transparency, and Tamper resistance are key features of Blockchain.In this paper we collected and defined Quality of Service metrics for Blockchains that drive their key characteristics.We also review and evaluate BlockSim and VIBES as Blockchain simulators to study the effect of Blockchain configuration parameters on Blockchain Quality of Service metrics.
Empirical power consumption characterization and energy aware scheduling in data centers

Energy-efficient management is key to reduce operational cost and environmental contamination in modern data centers. Energy management and renewable energy utilization are strategies to optimize energy consumption in high-performance computing. In any case, understanding the power consumption behavior of physical servers in datacenter is fundamental to implement energy-aware policies effectively. These policies should deal with possible performance degradation of applications to ensure quality of service. This manuscript presents an empirical evaluation of power consumption for scientific computing applications in multicore systems. Three types of applications are studied, in single and combined executions on Intel and AMD servers, for evaluating the overall power consumption of each application. The main results indicate that power consumption behavior has a strong dependency with the type of application. Additional performance analysis shows that the best load of the server regarding energy efficiency depends on the type of the applications, with efficiency decreasing in heavily loaded situations. These results allow formulating models to characterize applications according to power consumption, efficiency, and resource sharing, which provide useful information for resource management and scheduling policies. Several scheduling strategies are evaluated using the proposed energy model over realistic scientific computing workloads. Results confirm that strategies that maximize host utilization provide the best energy efficiency.
A Neural Network in Convolution with Constant Error Carousel Based Long Short Term Memory for Better Face Recognition

Unconstrained face identification, facial periocular recognition, facial land marking and pose prediction, facial expression recognition, 3D facial model design, and other facial-related problems require robust face detection in the wild. Despite the fact that the face recognition issue has been researched intensively for decades with different commercial implementations, it nevertheless faces problems in certain real-world scenarios due to multiple obstacles, such as severe facial occlusions, incredibly low resolutions, intense lighting, exceptionally pose inconsistencies, picture or video compression artefacts, and so on. To solve the problems described above, a face detection technique called Convolution Neural Network with Constant Error Carousel dependent Long Short Term Memory (CNN-CEC-LSTM) is proposed in this paper. This research implemented a novel network structure and designed a special feature extraction that employs a self-channel attention (SCA) block and a self-spatial attention (SSA) block that adaptively aggregates the feature maps in both channel and spatial domains to learn the inter-channel and inter-spatial connection matrices; additionally, matrix multiplications are conducted for a This approach first smoothed the initial image with a Gaussian filter before measuring the gradient image. The Canny-Kirsch Method edge detection algorithm was then used to identify human face edges. The proposed method is evaluated against two recent difficult face detection databases, including the IIT Kanpur Dataset. The experimental findings indicate that the proposed approach outperforms the most current cutting-edge face recognition approaches.
Sistem Informasi Bimbingan Belajar Berbasis Web dengan Metode Waterfall

The creation of a web-based information system at the North Jakarta Sunter branch of Kumon tutoring is intended to improve service quality and quality in the implementation of teaching and learning activities. Based on this, this study will develop a web-based information system that includes an interface design, namely the main page, login, subjects, schedule of subjects, and grades. Making this system an effort to optimize service performance to students.Keywords:Web Design Application, Design and Implementation Application Information Systems
Fuzzy Based Stable Maintainability Metric for Software Projects

To make software better in view of its maintainability, its software development process must be controlled and continuously observed. Researchers and software managers have stressed on the early measurement of maintainability starting from design phase itself so that timely steps could be taken for producing maintainable software. This paper evaluates and compares several methodologies for improving the numerical stability of a fuzzy-logic-based maintainability metrics system. Fuzzy parameters are adjusted using heuristic methods. A number of alternates were considered, in which training data sets were generated using different methods and these sets were used to evaluate objective functions in GA and accordingly fuzzy parameters were tuned. After conditioning, real projects’ maintainability data is used to show that fuzzy model performance is increased, however marginally, after conditioning
DISK-CSV: Distilling Interpretable Semantic Knowledge with a Class Semantic Vector

Neural networks (NN) applied to natural language processing (NLP) are becoming deeper and more complex, making them increasingly difficult to understand and interpret.Even in applications of limited scope on fixed data, the creation of these complex "black-boxes" creates substantial challenges for debugging, understanding, and generalization.But rapid development in this field has now lead to building more straightforward and interpretable models.We propose a new technique (DISK-CSV) to distill knowledge concurrently from any neural network architecture for text classification, captured as a lightweight interpretable/explainable classifier.Across multiple datasets, our approach achieves better performance than the target black-box.In addition, our approach provides better explanations than existing techniques.
Conceptual Framework of Kxpert:Knowledge-Based Information Retrieval for Expert Profiling

With the constant demand for expertise within organisation, especially in boosting the credibility of experts in the organisation, it is a need to bring forth a simple yet effective knowledge-based expert profiling based on information retrieved from credential publication sites. A number of frameworks from previous authors are analysed to propose one sound framework for a case university, to improve its existing research expert database, to make it more efficient in the information retrieval process and knowledge repository technique. Knowledge expertise mapping is proposed to be part of the whole mechanism for the conceptual framework called kXpert in this paper. The choice of credential knowledge sources is highlighted due to the updated information made available on the sites that are based on the published works of the internal experts. Very rare that this information is referred to on daily basis when there is a need to find expertise, thinking that the existing database has it all. The proposed conceptual framework presented in this paper is the work to be completed in the next phase, and can be customised for other organisations, industries and purposes.
WEBQUEST AS A MEANS OF MOTIVATING FUTURE PRIMARY SCHOOL TEACHERS TO PROFESSIONAL ACTIVITY

The article analyzes the peculiarities of WebQuest technology application as a means of motivating future primary school teachers to work. The content of concepts “WebQuest”, “WebQuest technology” has been considered. The main stages of work on WebQuest, features of its creation in the Internet have been described. The necessity of introduction of web-technologies into the educational process of higher educational institutions, which promote the formation of motivation future primary school teachers to professional activity, has been substantiated. The methodological basis of the study is a systematic approach to the study of pedagogical science provisions in the WebQuest application. The WebQuest is viewed as an innovative resource-oriented technology aimed at students’ independent search for information required to perform a problem task using Internet resources. It is determined that the WebQuest integrates elements of project, game, problem, and group learning and creates prerequisites for the transformation of new data obtained by students into new knowledge that they can use in their future professional activity. The didactic possibilities of the WebQuest technology for increasing motivation of students of specialty 013 Primary education to the professional activity, formation of their motivated attitude to the teaching, desire to work with high adaptability and flexibility have been described.It is found out that motivation to professional activity is a set of actions of concrete impulse (motives, needs, interests, aspirations, incentives, attitudes, value orientations), which determine the choice of primary school teacher’s profession and long-term performance of duties related to this profession. It has been proved that the application of WebQuest technology creates favorable conditions for the formation of future specialists’ motivations to professional activity, their attitude to independent and systematic updating of knowledge and its effective application in practice.
Feature Interactions in Highly Configurable Systems: A Dynamic Analysis Approach with Varxplorer

Highly-configurable systems provide significant reuse opportunities by tailoring system variants based on a set of features. Those features can interact in undesired ways which may result in faults. Thus, we propose VarXplorer, a dynamic and iterative approach to detect suspicious interactions. To evaluate whether VarXplorer helps improving the performance of identifying suspicious interactions, we performed two empirical studies. Our results shows that from the VarXplorer graphs, participants are able to identify suspicious interactions more than 3 times faster compared to the state-of-the-art tool. Additionally, the iterative detection process provides a more efficient feature interaction analysis, reducing the data developers needs to check to find problematic interactions.
SUSAN: The Structural Similarity Random Walk Kernel

Random walk kernels are a very flexible family of graph kernels, in which we can incorporate edge and vertex similarities through positive definite kernels.In this work we study the particular case within this family in which the vertex kernel has bounded support.We motivate this property as the configurable flexibility in terms of vertex alignment between the two graphs on which the walk is performed.We study several fast and intuitive ways to derive structurally aware labels and combine them with such a vertex kernel, which in turn is incorporated in the random walk kernel.We provide a fast algorithm to compute the resulting random walk kernel and we give precise bounds on its computational complexity.We show that this complexity always remains upper bounded by that of alternative methods in the literature and study conditions under which this advantage can be significantly higher.We evaluate the resulting configurations on their predictive performance on several families of graphs and show significant improvements against the vanilla random walk kernel and other competing algorithms.
The Effects of Agile Methodologies on Software Project Management in Pakistani Software Companies

Agile methodologies are always tends to increase the quality of software and also handling the complex software projects. However, the software companies in Pakistan have recently felt the disparity of producing successful software. In this context, an extensive survey has been conducted in 52 prominent software development companies of Pakistan to identify this remedy and the motivation behind this production discrepancy. It is revealed from the survey that there is a lack of empirical evidence in the relationship of agile methodologies with the effective and progressive management of software project management factors including, schedule, scope, risk, budget, quality and resources. Therefore, the proposed study delivers an extensive statistical comparison to determine the effectiveness of agile methodologies in terms of their effects on the project management factors. The results suggest that in general all agile methodologies play a significant role towards the successful software development in the software company. However, Extreme Programming, Scrum, Kanban and Agile modeling are the main determinants of production disparity among software companies. Furthermore, it is determined that the quality factor has a positive correlation with the rest of the factors. It is also found that the budget factor has significantly correlated with other five factors, while rest of the factors has insignificant correlation. We have also compared agile methodologies in terms of project management factors, which specify that each agile methodology has its own importance and effect with respect to managing different factors of project management.
Detecting Phishing Attacks using NLP

In present world phishing attacks are the most common and easily targeted attacks. In order to analyse texts and detect improper statements that show the phishing attacks, we have come with an idea which will use (NLP) Natural language processing techniques. Compared to previous work, our approach is different because the emphasis is on the text data found in the attack, which is semanticized in order to identify malicious intent. We have evaluated it using a huge phishing e-mail test data to illustrate the efficacy of our strategy.