Reviewerly/exHarmony huggingface dataset:
GLEncObfus-Encryption and Obfuscation Technique to Enhance Data Protection in Public Cloud Storage

There is a rapid increase in data volume all over the world. In the computer network world also, imminent changes are happening. Under any circumstance, data can be vulnerable from one’s own side or by a service provider or on data movement. In that case we need to secure our data. In this paper, the improved methods of protection against data leakage has been discussed. Public cloud data theft can happen through intruders or hackers or service providers. The data securing algorithm are used prior to storing the data in the server. Any data entering the cloud area is segregated into numerical and non-numerical parts, where non-numeric is operated by one algorithm and obfuscation method is applied on the numeric part. These two operations are done simultaneously with different threads. This both works come together and developed an entirely different algorithm. Hence the proposed algorithm maximizes the security and reduces the service cost. The proposed method is implemented as a cloud application and hosted on a cloud platform as a service and tested by subsisting present methods with respect to time and security levels. From the results, it is observed that the proposed method GLEncObfus is more efficient than present methods with reference to encryption-obfuscation time, decryption-de-obfuscation time and security level.
Lemp: a Robust Image Feature Descriptor for Retrieval Applications

line edge magnitude pattern (lemp) is proposed in this paper. Line edge distribution is used to denote local region of an image. Popular texture descriptors such as lbp deal with a comparison of centre pixel with neighbors and thus encode the information. In lemp ,pixel at the centre is replaced by edge values of neighbors. Discriminating information provided by line edges makes this method different from many of the existing methods. Magnitude is also added to the line edge information in order to make the feature descriptor more effective and robust. Performance of lemp method is estimated with corel database. Standard metrics such as recall, precision and average retrieval rate are determined for comparison purpose. Experimental values exhibit a notable improvement in the performance.
Impact of Organizational Justice (Distributive Justice, Procedural Justice, and Interactional Justice) on Job Satisfaction

Perceptions of organizational justice constitute an important heuristic in organizational decision-making, as research relates it to job satisfaction, turnover, leadership, organizational citizenship, organizational commitment, trust, customer satisfaction, job performance, employee theft, role breadth, alienation, and leader-member exchange. The public sector in UAE is the focus of this paper. Applying the concept of organizational justice (distributive justice, procedural justice, interactional justice) to examine the effect of it on employees’ satisfaction. The data was collected from 452 officers from 7 sectors in the ministry of interior in UAE and analysed using structural equation modelling via SmartPLS 3.0. There were three main results: first, distributive justice has a positive impact on job satisfaction; second, procedural justice is significantly predicting job satisfaction; third, interactional justice has a significant impact on job satisfaction. The proposed model explained 33.7% of the variance in job satisfaction. Theoretical and practical implications are also provided
Designing Graph Database for Managing Lecturers Scientific Publications Using Neo4j

This study aimed to implement a database design to manage lecturers’ scientific publications using a graph database. Data of lecturers' scientific publications are very important to be managed properly. These data are much needed as the requirement of university accreditation, university clustering, and proposal of lecturers’ functional positions. The increasing number of data certainly requires a good database design and one of the alternative databases is a graph database which is a model of a NoSQL database. This study was conducted in several stages: data collection and analysis, conceptual level database design, logical level database design, and physical level database design. This study developed a graph database design that stored various data about lecturers' scientific publications using Neo4j.
An enhanced cuckoo search using dimension selection

This paper proposes an enhanced cuckoo search algorithm using dimension selection. In the proposed strategy, the dimensional distance measure is used to select a part of dimensions of each solution to search for the new solution in two search components. The dimensions of each solution are selected when those dimensional distances are larger than the average distance of all dimensional distance. A suit of 20 benchmark functions are employed to verify the performance of the proposed algorithm, and the results show the improvement in effectiveness and efficiency of dimension selection.
ZenoString: A Data Structure for Processing XML Strings

This paper describes a novel data structure for the representation of Unicode strings, designed to efficiently support the usage patterns that arise when processing XML using languages such as XSLT, XPath, and XQuery.
The Effects of Anxiety and Emotional Intelligence on The Mathematic Learning Outcomes of Fifth Grade Students

Students experience very high anxiety, so it impacts the difficulty of digesting and understanding mathematics learning materials. It causes low Mathematics learning outcomes. This study analyzes the effect of anxiety and emotional intelligence on fifth-grade elementary school students' mathematics learning outcomes. This study was an "ex post facto" study with a population of 238 students. The sample was determined using a proportional random sampling technique to obtain a total sample of 142 students. The techniques used to collect data were observation, interviews, questionnaires, document recording, and tests. The instrument used to collect data was a questionnaire. Hypothesis testing was carried out using simple regression analysis techniques and multiple regression analysis. The results of this study indicate that: There is an influence of anxiety on mathematics learning outcomes with a contribution of 3.5%; There is an influence of emotional intelligence on mathematics learning outcomes with a contribution of 6.6%; There is an influence of anxiety and emotional intelligence on mathematics learning outcomes with a contribution of 7.2%. So the conclusion of the research shows a significant influence between anxiety and emotional intelligence on the mathematics learning outcomes of fifth-grade elementary school students.
Cloud Computing: Elementary Threats and Embellishing Countermeasures for Data security

Internet offers bunch of services and resources, one of them is cloud computing. The centers which provide these services are located all around the world and this service has its own mainstream pros and cons. Cloud computing consists of taking cloud services from the internet and taking them away from the considerable firewall. This paper aims in enhancing specifications of cloud computing, review its security threats and address security concerns along with the cloud operations that needs security. Also, this paper addresses basic security models, qualities and prerequisites for cloud Computing
Biogeochemistry using Melastoma Malabathricum and fern from mineralised area in Sokor, Kelantan

This research is about biogeochemistry which investigates the relationship of heavy metals concentration contained within plants versus soil samples in the selected area of Sokor, Kelantan. The identified lithology of the study area is argillaceous and calcareous units and the geological structures of folding which contribute to the current bed dipping and hydrothermal alteration through joint infilling has indicated an ore deposit region. Four sets of soil and plant samples had been collected and characterized through X-Ray Diffraction, X-Ray Fluorescence and Inductively Coupled Plasma Mass Spectrometry respectively. The main composition of soil is clay minerals, kaolinite, dickite and pyrophyliite which can indicate argillic alteration and possible supergene enrichment for ore deposition. Phyllic alteration has also been found in area close to the study area with mineral assemblage of pyrite, quartz and sericite. A relationship between the geomorphology, plant morphology and the ore element content in the soil also have been discussed. The metal elements concentration is found higher in lower elevation except aluminium and iron; the differential morphology of Melastoma Malabathricum can indicate iron concentration in the soil.
Emotions Identification by Using Unsupervised Aspect Category Based Sentiment Classification

The social media is growing at an astonishing rate; this has resulted in increased online communications. The online communication contains feedbacks, comments, and reviews that are posted on the internet by users. To analyze such data, the paper represents the Aspect-based unsupervised method that applies association rule mining on customer reviews aims to algorithmically identify product aspects, their corresponding opinions from a collection of opinionated reviews. This framework involves four main subtasks: Product aspect identification, Sentiment expression identification, Emotion Detection, Comparison of Products. This paper also represents a Comparative study of sentiment analysis techniques including machine learning technique and lexicon based technique. The comparisons are majorly drawn based on features such as techniques, data source, data scope, and limitations. The proposed framework performs well with F1-Score 76.426%.
Modified Boundary Matching algorithm for Error detection and Error Concealment for Video Communication

As the demand of video transmission over communication network has grown rapidly, the data compression and error correction in video processing have shown significant improvement day by day. When the error occurs in a single frame, the visual quality of the subsequent frames gets degraded due to error propagation. Thus, the error control techniques are required for the recovery. Concealment of error at the receiver (decoder) side feats the spatial and temporal characteristics of the frame. Without the requirement of the extra bandwidth and retransmission delay, it enhances the quality of the reconstructed video. However, the output of the error concealment may get affected if the error located before is misleading. Thus error detection also plays an important role while reconstructing the video. However, the output of the error concealment may get affected if the error located before is misleading. This paper proposes error detection and concealment approach for the recovery of lost Macro Block (MB) in video. The spatio-temporal techniques has been used for the error detection followed by the MB type decision applied for classifying the damaged macro block .For the concealment method a new method i.e. Modified Spatio-Temporal Boundary Matching Algorithm (MSTBMA) has been proposed. The proposed work is compared with various existing method for spatial and temporal error concealment. The comparison has been done for various types of error such as block error (single, multiple), burst error and random error generated by the software. Performance is improves in terms of PSNR and visual quality by considering the type of lost MB.
ETHICAL HACKING

Ethical Hacking is done by companies in anticipation of system security loopholes. Ethical hacking is done by someone who has the ability like a hacker who is able to attack a system but has the motivation to help companies find security gaps that companies will use to evaluate their systems. This paper explains the importance of information and why it must be maintained and how an ethical hacker does his work.
Effect of natural organic acids on mobilization of macro- and microelements from rocks

Experimental study of leaching of the main cations (Na, K, Mg, and Ca), alkaline and alkaliearth microelements (Li, Rb, Cs, Be, Sr, and Ba), heavy metals (Mn, Fe, Co, Ni, Cu, Zn, Cd, Tl, and Pb), hydrolyzate elements (Y, RZ, Ti, Th, and U), and anionic elements (F, Si, P, and V) from rocks of different acidity with distilled water and a multicomponent solution of organic acids, having the distribution of dissociation constants corresponding to natural dissolved organic matter was carried out. It has been shown that carboxylic acids, which are part of the dissolved organic matter contained in surface waters, cause a sharp increase in the mobilization of both the main cations and trace elements from silicate rocks. The chemical properties of the elements are of secondary importance, as was shown by the general correlation between the parameter related to the mobility of the elements at the initial stage of the leaching and their content in the rocks.
Color Channel CAPTCHA: A Secure Scheme for Cloud Environment

Abuse of cloud services consequently unauthorized access to cloud data by malicious software automation is prevented by CAPTCHA. The secure usable mechanism is mandatory for resilience to automate attacks accordingly to create pleasant challenges. In this paper, we propose a novel image-based graphical Color Channel CAPTCHA scheme to distinguish between malware and humans for data security in the cloud environment. This color channel CAPTCHA is designed with 2 X 2 grids of different color channels with micro invisible circles or less visible moving circles. This simple challenge is completed by click on the specified circles in the given order with very less solving time, while compared to the state of the art. The experimental study has been conducted among 41 participants on both usability and performance of color channel CAPTCHA.
New Normal: Pengembangan Sistem Informasi Penjualan Menggunakan Metode SDLC (System Development Life Cycle)

The world of information technology is currently developing very rapidly to enter various activities, activities and human life. Including one of them in the company CV. ABSystem.co.id sells software products, in the form of applications, websites, domain hosting and various other application products. CV. ABSystem.co.id previously had a website that contained a complete company profile, access to blogging, product sales and customer service. Many customers don't know how to process the product purchase and there are still many who contact the admin. This research uses the SDLC (System Development Life Cycle) method as well as the PHP and MySql programming languages. The results of this research are in the form of website development in helping and making it easier for admins and customers, the accuracy of the development of this sales information system with the blackbox method with successful trial results from the login display to enter the username and password, the display of the category input form to enter a new product category, the display of the input form. The product enters a new product, the order mutation display shows the purchase transaction data, the change password view displays the page for changing the password, the menu view displays the home page, the product detail view displays the product detail page, the cart detail view displays the contents of the shopping cart, the checkout view displays the product order form , The testimonial menu display includes criticism of consumer suggestions, The about us menu displays company information.
Combating credit card fraud with online behavioural targeting and device fingerprinting

There are many existing fraud detection techniques employed by card issuers and researchers globally. Despite this evolution of several fraud detection techniques, billions of dollars are still lost due to credit/debit card fraud every year. This paper proposes a fraud detection framework that uses online behavioural targeting (OBT) data and device fingerprinting (DF) to improve the efficiency of the fusion approach using Dempster-Shafer theory and Bayesian learning. OBT and DF provide massive insights into our online behaviour and can be used to pinpoint fraudsters as well as know shopping patterns of credit card users. These technologies are able to track and profile Internet users up to the level of what device they are using and what they are most likely to purchase. The paper also presents the theoretical underpinnings of the framework and its application scenarios.
Merging Artificial Intelligence and Blockchain Technologies to Solve Academic Qualification Forgery Issues

This paper emphasizes the possibility of merging artificial intelligence and Blockchain technologies to solve academic qualifications forgery issues in the educational sectors. Empirical data is collected through interviews with specialists and technical people who are interested in the emerging technologies of the Fourth Industrial Revolution and focus group discussions in the field, as well as from reports in the reviewed literary articles. Scientific journals have also been accessed to analyse the paper goals and objectives. The findings suggest that emerging technologies can be integrated to become more efficient and effective in detecting fraud and forgery before it occurs. Considerable attention should be given to reducing and combating these issues because they have significant negative impacts on the economy and education. Accordingly, the study makes recommendations based on the results and areas of future research, considering the establishment of a unified and integrated system. Initially it will be applied as a pilot in Sultanate of Oman, then gradually it will be extended to the Gulf Cooperation Council States (GCC) and internationally particularly the affiliated and the recognized educational institutions to avoid the phenomena that affects the reputation and quality of education institutions and academic qualifications. The conclusion considers the impacts of the proposed system in the education and economy as well in general.
Symbolic Computing

Symbolic computation refers to using machines or computers to manipulate mathematical equations and expressions in symbolic form, as opposed to numerical manipulation.Using symbolic computing to solve mathematical problems involves manipulations of symbolic objects, rules or programs, with the main goal of being exact.This is unlike most numeric calculations where computations use approximate floating point arithmetic.This paper provides a brief introduction to symbolic computing, its applications, benefits, and challenges.
Off-line Sindhi Handwritten Character Identification

Handwritten Identification is an ability of the computer to receive and translate the intelligible handwritten text into machine-editable text.It is classified into two types based on the way input is given namely: off-line and online.In Off-line handwritten recognition, the input is given in the form of the image while in online input is entered on a touch screen device.The research on off-line and online handwritten Sindhi character identification is on its very initial stage in comparison to other languages.Sindhi is one of the subcontinent's oldest languages with extensive literature and rich culture.Therefore, this paper aims to identify off-line Sindhi handwritten characters.In the proposed work, major steps involve in characters identification are training and testing of the system.Training is performed using a feed-forward neural network based on the efficient accelerative technique, the Back Propagation (BP) learning algorithm with momentum term and adaptive learning rate.The dataset of 304 Sindhi handwritten characters is collected from 16 different Sindhi writers, each with 19 characters.The novelty of proposed work is the comparison of the recognition rate for the single character, two characters and three characters at a time.Results showed that the recognition rate achieved for a single character is more than the recognition rate of multiple characters at a time.
Image Squeezing By The Wavelet Squeezing

the problem of effective compression and transmission of images remains one of the most important in the field of multimedia technologies and is very promising in recent years. The article attempts to give its own interpretation of this problem and to analyze the features of the existing methods of wavelet transform, as well as to present software designed for compression of images for their compact storage and transmission through communication channels at maximum speed.
A Media Architecture Approach for Designing the Next Generation of Urban Interfaces

The augmentation of the built and urban environment with digital media has evolved and matured over recent years. Cities are seeing a rapid rise of various technologies; a trend also accelerated by global crises. Consequently, new urban interfaces are emerging that integrate next-generation technologies, such as sustainable interface materials and urban robotic systems. However, their development is primarily driven by technological concerns, leaving behind social, aesthetic, and spatial considerations. By analyzing our own media architecture research projects and real-world applications from the past two decades, we offer a structural approach for developing these new urban interfaces. The individual cases provide early insights and challenges related to prototyping and augmenting contexts with novel input and output modalities. These results in common, preliminary observed patterns in the process of integrating next-generation technologies into urban environments and surroundings, in response to continuously evolving social needs.
The Role of Kinematic Properties in Multiple Object Tracking

[Introduction] People commonly track objects moving in complex natural displays and their performance in the “multiple object tracking” (MOT) paradigm has been used to study this visual attention task for over three decades. Given the theoretical and practical importance of object tracking, it is critical to understand how people solve the correspondence problem to track objects; however, it remains unclear what information people use to achieve this feat. In particular, while people can track multiple moving objects based on their positions, there is ambiguity whether people can track objects via higher order kinematic information such as velocity. [Method] We explicitly test whether people can use instantaneous velocity direction to solve the correspondence problem during multiple object tracking when positional information is completely ambiguous. And we further test whether acceleration direction can also be used for tracking when object position and instantaneous velocity direction are both uninformative. [Results] We show that people use velocity direction when it is necessary to disambiguate targets from distractors. However, tracking via velocity is less accurate than tracking via position alone, indicating that velocity simply does not provide as an informative cue as position. Furthermore, observers fail to use acceleration to track objects, even though they can reliably detect the acceleration cue. This pattern of results indicates that the failure to use acceleration during object tracking reflects which kinematic information is used to resolve correspondence. Finally, we demonstrate that the extent to which velocity, but not acceleration, is used varies with “kinematic load” – the number of object pairs requires velocity information simultaneously. Together, these results indicate a hierarchy of kinematic information for tracking – position is most precise and most useful, but velocity can still be used to solve the correspondence problem; acceleration, in contrast, seems to be largely not used for multiple object tracking.