Reviewerly/exHarmony huggingface dataset:
A Survey on Cloud Data Security using Image Steganography

Now-a-days, cloud computing proved its importance where it is being used by small and big organizations.The importance of cloud computing is due to the various services provided by the cloud.One of these services is storage as a service (SaaS) which allows users to store their data in the cloud databases.The drawback of this service is the security challenge since a third party manages the data.The users need to feel safe to store their data in the cloud.Consequently, we need for models that will enhance the data security.The image steganography is a way to protect data from unauthorized access.Image steganography allows users to conceal secret data in a cover image.In this paper, we review and compare some of the recent works proposed to protect cloud data using image steganography.The first comparison of models based on the algorithms they used, advantages and drawbacks.The second comparison of the models based on the aims of steganography: quality where the model produces a stego-image with high quality, security where the secret data is difficult to detect and capacity where the model allows to hide large amounts of data.
Dishing the Deets: How Dark-Web Users Teach each other about International Drug Shipments

International trafficking of drugs enabled by the dark-web is still a problem despite the increase in takedown actions.Even though the transaction takes place digitally, the national postal systems are the ones being exploited and used for delivery.Users of the dark-web readily share information on forums, cryptomarkets, and feedback pages to maximize their safety and success while conducting these drug transactions.Using data collected from forums, vendor profiles, and feedback pages, this study provides an evidence that the knowledge being shared on the dark-web is rich data law enforcement and governments need to use as intelligence.Users discuss all aspect of the delivery process, including proper addressing, stealth packaging, and risks associated with taking delivery of the package.Based on these findings, policy recommendations are made to guide the implementation of techniques to counter the rise of dark-web-enabled drug shipments in the fight against drugs and cryptomarkets.
APLIKASI KEAMANAN DOCUMENT DIGITAL MENGGUNAKAN ALGORITMA STEGANOGRAFI DISCRETE COSINE TRANSFORM (DCT) PADA PERUSAHAN ALAT BERAT

Electronic documents are information that is permitted or stored in a way that is requested by a computer or other electronic device to be installed, assigned or processed. These documents consist of text, graphics or spreadsheets. For the current technological developments that improve progress, security is very important in companies that are difficult to avoid the follow-up of information by parties who are not responsible. One method that can be used to obtain digital documents is using Steganography and Cryptography technology by using Discrete Cosine Transform (DCT) technology and Advanced Desktop Encryption Standard (AES-192) algorithm based on Java Desktop. The purpose of this application is to prepare data or files to be hidden on the cover image of the file. Before inserting with the closing image file, the file is encrypted with a symmetrical key using the AES-192 algorithm. The benefits obtained in this application, the confidentiality of information or data on this heavy equipment company can be difficult with good and safe. With this application it is expected to help the confidentiality of information or data on heavy equipment companies. .
Container and VM Visualization for Rapid Forensic Analysis

Most cloud security incidents are initially detected by automated monitoring tools.Because they are tuned to minimize the risk of false-negative errors, these tools cast a wide net of suspicion.Depending on the scale of the incident, the automated tools may implicate rather long lists of VMs and containers.Hence, this study proposes a new intermediate step aimed at reducing the number of VMs and containers awaiting forensic investigation.The proposed method renders two-dimensional visualizations of container contents and virtual machine disk images.The visualizations can be used to fingerprint container / VM contents, pinpoint instances of embedded malware, and find modified code.The proof of concept is evaluated in a pilot study.The results indicate that it shows promise.Implications and future research directions are also described.
The 2018 ACRL Academic Library Trends and Statistics Annual Survey: Survey results and how to use them

The editorial board of the ACRL Academic Library Trends and Statistics (ALTS) Annual Survey is thrilled to announce a 19.8% increase in survey participation over the past 4 years. Along with this increased participation comes a better understanding of what is happening in academic libraries and more impactful data for participants and researchers. Survey participants receive a complimentary link to summary data on the ACRLMetrics website. A subscription to ACRLMetrics provides access to all ALTS data starting from 1999 to present. A print edition of the 2018 data is also available for purchase through the ALA Store. This article highlights some of the findings from the 2018 survey and identifies valuable ways the data from the survey can be used.
Penerapan Clustering Pada Laju Inflasi Kota Di Indonesia Dengan Algoritma K-Means

Inflation is a process of increasing prices in general and continuously, related to market mechanisms that can be caused by various factors, among others, increased public consumption, excess liquidity in the market which triggers consumption or even speculation, to include the consequences of inability to distribute goods. Inflation is an indicator to see the level of change, and is considered to occur if the process of price increases takes place continuously and influences each other. Inflation stability is a prerequisite for sustainable economic growth which ultimately benefits the improvement of people's welfare. With the large amount of data generated from the inflation rate of cities in Indonesia it is difficult for the government to classify the inflation rate. The author took the initiative to conduct research on classifying the inflation rate of cities in Indonesia by using the K-Means Clustering Data Mining algorithm, with the number of clusters being 3. The high value group is in cluster 1 (above average), the value group is in cluster 2 (around the average based on the distance used from the centroid), and the low value group is in cluster 3 (below average). flat). By grouping the rate of inflation of cities in Indonesia, it will be known which cities in Indonesia have high, medium and low inflation rates.
The Modernisation of Historical Education in a Higher Engineering School (The Case of Tomsk Polytechnic University)

И.Ю. Гурьева, А
A New Solution to Protect Encryption Keys when Encrypting Database at the Application Level

Encrypting databases at the application level (client level) is one of the most effective ways to secure data.This strategy of data security has the advantage of resisting attacks performed by the database administrators.Although the data and encryption keys will be necessarily stored in the clear on the client level, which implies a problem of trust viz-a-viz the client since it is not always a trusted site.The client can attack encryption keys at any time.In this work, we will propose an original solution that protects encryption keys against internal attacks when implementing database encryption at the application level.The principle of our solution is to transform the encryption keys defined in the application files into other keys considered as the real keys, for encryption and decryption of the database, by using the protection functions stored within the database server.Our proposed solution is considered as an effective way to secure keys, especially if the server is a trusted site.The solution implementation results displayed better protection of encryption keys and an efficient process of data encryption /decryption.In fact, any malicious attempt performed by the client to hold encryption keys from the application level cannot be succeeded since the real values of keys are not defined on it.
Stemming Text-based Web Page Classification using Machine Learning Algorithms: A Comparison

The research aim is to determine the effect of word-stemming in web pages classification using different machine learning classifiers, namely Naïve Bayes (NB), k-Nearest Neighbour (k-NN), Support Vector Machine (SVM) and Multilayer Perceptron (MP).Each classifiers' performance is evaluated in term of accuracy and processing time.This research uses BBC dataset that has five predefined categories.The result demonstrates that classifiers' performance is better without word stemming, whereby all classifiers show higher classification accuracy, with the highest accuracy produced by NB and SVM at 97% for F1 score, while NB takes shorter training time than SVM.With word stemming, the effect on training and classification time is negligible, except on Multilayer Perceptron in which word stemming has effectively reduced the training time.
The Effect of the Mind Mapping Strategy on the L2 Vocabulary Learning of Saudi Learners

The aim of this study was to investigate the impact of using the mind mapping strategy on learning vocabulary for Saudi Learners. Fifty female students from the English Language centre at Taibah University in Saudi Arabia were selected to participate in this study. All students were homogenous in terms of their English language proficiency. The students were performing at the intermediate level of the English language. Their level of English language proficiency was determined by the Oxford Placement Test. Participants were divided into two groups: the experimental group and the control group. Twenty-five students in the experimental group were taught vocabulary using the mind mapping strategy for six weeks. The control group was taught using traditional methods of vocabulary teaching, such as memorising. To test the effectiveness of the mind mapping strategy, two types of tests were applied for both groups: a pre-test and a post-test. At the end of the treatment, the results of the post-test showed a significant improvement in Second language (L2) vocabulary acquisition by Saudi learners in the experimental group. The findings of this study indicate some important implications for L2 learning, such as that mind mapping facilitates vocabulary learning by increasing the knowledge and the acquisition of the meanings of the vocabulary words used. It also helped with the vocabulary learning process by increasing the level of the motivation of Saudi students in learning new words.
About the Measuring of Information Security Awareness: A Systematic Literature Review

To make employees aware of their important role for information security, companies typically carry out security awareness campaigns.The success and effectiveness of those campaigns has to be measured to justify the budget for example.Therefore, we did a systematic literature review in order to learn how information security awareness (ISA) is measured in theory and practice.We covered published literature as well as unpublished information.The unpublished information was retrieved by interviewing experts of small and medium-sized enterprises.The results showed that ISA is mostly measured via questionnaires.Round about 40 % of the questionnaires are based on the Knowledge-Attitude-Behavior-Model which is itself scientifically weak.According to studies measuring knowledge is not sufficient and,behavior has to be measured.Our results show that the answers of participants in questionnaires often differ from the truth due to wrong perception or social desirability bias.Therefore, behavior should be measured through behavior tests.
Towards interpretable, data-derived distributional semantic representations for reasoning : A dataset of properties and concepts

This paper proposes a framework for investigating which types of semantic properties are represented by distributional data. The core of our framework consists of relations between concepts and properties. We provide hypotheses on which properties are reflected in distributional data or not based on the type of relation. We outline strategies for creating a dataset of positive and negative examples for various semantic properties, which cannot easily be separated on the basis of general similarity (e.g. fly: seagull, penguin). This way, a distributional model can only distinguish between positive and negative examples through evidence for a target property. Once completed, this dataset can be used to test our hypotheses and work towards data-derived interpretable representations.
Male and Female Strategy in reading Comprehension of Narrative text at Sma Kampus FKIP Universitas HKBP Nommensen Pematangsiantar

─The purpose of this research is to analyze Male and Female Strategy in Reading Comprehension of Narrative Text in SMA Kampus FKIP Universitas HKBP Nommensen Pematangsiantar.The results of this study showed that (1) There were Seven Top down Strategy.(2) There were Eight Bottom up Strategy.( 3) There were Five Interactive Strategy.Based on the results of research conducted, the researcher is find out male and female students' strategy in reading comprehension, namely from the results of essay text research and questionnaire texts that male students are more use top down strategies in reading comprehension while female students are more use bottom up strategies in reading comprehension, namely from the results of essay text research and questionnaire texts, and there are some male and female students in using interactive strategies.The research result shown that the male students have a slight difficulty and relatively similar in understanding the Text.
Pemetaan Topografi Calon Lokasi Embung di Kampus IPB Darmaga, Bogor

Before planning and designing a small dam, land’s topographic mapping and water flow pattern’s analysis are needed. The aim of this research were to identify the land use, water catchment areas, water flow pattern, and analyze land’s topographic condition, as well as producing topographic maps and calculating inundation volume at small dam location at IPB Campus Darmaga. This research was conducted in April - July 2019. The land use around the small dam location consisted of forests, roads, grasslands, bare land, settlements, and agriculture lands. The catchment area of the small dam location was divided into four area, with an area of 2881.0 m2, 4531.0 m2, 2790.0 m2, and 10917.3 m2 respectively. The highest and lowest elevations based on land measurements at small dam location were 199.71 masl and 187.23 masl. The topographic map was created using Surfer 13 software with the most appropriate interpolation method was natural neighbor. The direction of the surface water flow was relatively uniform and leads to the North and South. The minimum and maximum of inundation volume were 1.5 m3 and 13752.8 m3, and the optimum inundation volume was 2824.8 m3.
An Enhanced K-Nearest Neighbor Predictive Model through Metaheuristic Optimization

Retracted: After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IJACSA`s Publication Principles. We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
New Approach to Edge Detection on Different Level of Wavelet Decomposition

This paper proposes a new approach to edge detection on the images over which the wavelet decomposition was done to the third level and consisting of different levels of detail (small, medium and high level of detail). Images from the BSD (Berkeley Segmentation Dataset) database with the corresponding ground truth were used. Daubechies wavelet was used from second to tenth order. Gradient and Laplacian operators were used for edge detection. The proposed approach is applied in systems where information is processed in real time, where fast image processing is required and in systems where high compression ratio is used. That is, it can find practical application in many systems, especially in television systems where the level of details in the image changes. The new approach consists in the fact that when wavelet transform is applied, an edge detection is performed over the level 1 image to create a filter. The filter will record only those pixels that can be potential edges. The image is passed through a median filter that filters only the recorded pixels and 8 neighbors of pixel. After that, the edge detection with one of the operators is applied onto the filtered image. F measure, FoM (Figure of Merit) and PR (Performance Ratio) were used as an objective measure. Based on the obtained results, the application of the proposed approach achieves significant improvements and these improvements are very good depending on the number of details in the image and the compression ratio. These results and improvements can be used to improve the quality of edge detection in many systems where compressed images are processed, that is, where work with images with a high compression ratio is required.
Modify Manhattan Distance for Image Similarity

A New measure is proposed for assessing the similarity among gray-scale images. The well-known Structural Similarity Index Measure (SSIM) has been designed using a statistical approach that fails under significant noise (lowPSNR). The proposed measure, denoted by Manhattan distance and STD, uses a combination of two parts: the first part is the Geometric method, while the second part is based on the statistical feature. The concept of manhattan distance is used in the geometric part. The new measure shows the advantages of statistical approaches and geometric approaches. The proposed similarity method is an outcome for the human face. The novel measure outperforms the classical SSIM in detecting image similarity at low PSNR, with a significant difference in performance. AMS subject classification:
Information Analysis by Web Scraping Utilizing Python

The standard data examination are based on the root and effect relationship, molded a model little assessment, abstract and quantitative assessment, the reasonability approach of making extrapolation assessment. The Web Scraper's scheming morals and methods are compared, it clarifies about the working of how the scrubber is planned. Its strategy is assigned into three sections: the web scrubber draws the ideal connections from web, and afterward the information is separated to get the information from the source joins lastly stowing that information into a csv document. The Python language is actualized for the completing. Thusly, connecting all these with the ethical information on libraries and working ability, we can have a sufficientScraper in our grasp to deliver the ideal outcome.Because of a tremendous network and library assets for Python and the flawlessness of coding chic of python language, it is most suitable one for Scraping wanted information from the ideal site.
Performance Comparison of AODV and AOMDV Protocol Routing with TCP and UDP on Mobile Ad-Hoc Network (Manet) Using Malicious Node (Blackhole Attack)

Transmission package delivery can be a problem of routes on the network, one of them is the Wireless network. Mobile Ad-Hoc Network (MANET) topology is often used on Wireless networks. The existence of a malicious node is a threat to MANET. Package delivery uses AODV and AOMDV Protocol Routing in TCP and UDP packet transmission. This study uses a simulation method using NS2, NAM and AWK. The Quality of Service (QoS) parameters used are throughput, packet loss, and jitter. Simulations are carried out using malicious nodes, the results on the AOMDV TCP graph have the highest input values and the best packets but are difficult to minimize energy, while for the TCP jitter values graph is best because it has a flow control function that can adjust the trajectory. The results in AOMDV TCP have the highest input value and the best packet loss but it is difficult to minimize energy, while for TCP value jitters it is best because it has a flow control function that can adjust the trajectory
Knowledge Sharing Factors for Modern Code Review to Minimize Software Engineering Waste

Software engineering activities, for instance, Modern Code Review (MCR) produce quality software by identifying the defects from the code.It involves social coding and provides ample opportunities to share knowledge among MCR team members.However, the MCR team is confronted with the issue of waiting waste due to poor knowledge sharing among MCR team members.As a result, it delays the project delays and increases mental distress.To minimize the waiting waste, this study aims to identify knowledge sharing factors that impact knowledge sharing in MCR.The methodology employed for this study is a systematic literature review to identify knowledge sharing factors, data coding with continual comparison and memoing techniques of grounded theory to produce a unique and categorized list of factors influencing knowledge sharing.The identified factors were then assessed through expert panel for its naming, expressions, and categorization.The study finding reported 22 factors grouped into 5 broad categories i.e.Individual, Team, Social, Facility conditions, and Artifact.The study is useful for researchers to extend the research and for the MCR team to consider these factors to enhance knowledge sharing and to minimize waiting waste.
A Novel Method of Detecting Chinese Rendered Text on Tilted Screen of Mobile Devices

Due to the development of the Internet, screen rendered text detection and recognition have wide applications such as screen capture translation, medical text reading, screen text assisted reading and so on.A large number of screen-rendered attentions have been paid to the English text detection, multi-language scene detection and indefinite length recognition.However, these studies mainly focus on getting the screen rendered image from the device itself.In the actual scene, lots of screen rendered text is mainly captured by the mobile device, and text image has a certain capturing angle.Because of the tilted text line, the current method has a severe degradation in detection performance.This paper proposes a Chinese-style scene text detection method for tilting screens capturing by mobile devices.Firstly, in order to obtain robust detection performance, the Connectionist Text Proposal Network (CTPN) method is employed for horizontal text detection.Secondly, to overcome the dependence of detection on horizontal text, the lightweight Oxford Visual Geometry Group network (VGGnet) is used to correct the tilted direction of the whole image.Moreover, the word width of special characters and punctuation characters are far below average value, so this paper uses the Gaussian removal method to delete the narrow word width and designed a more accurate network to recognize characters.Experiments show that based on the comprehensive scheme, this paper achieves excellent results, even in some extreme bad cases.