Reviewerly/exHarmony huggingface dataset:
Digital Social Engineering Threatens Cybersecurity

This study aims to explore the role of social engineering in threatening cyber security by clarifying the concepts related to social engineering and its seriousness due to unlink to devices and equipment in general and its dependence on addressing the human psychic mechanisms known for curiosity. The study is based on the descriptive analysis studies that were based on the survey methodology using the questionnaire as a data collection tool, which was distributed to 98 respondents. The study found that the majority of the respondents had no idea about social engineering, and many of the females were rapidly clicking the links.. The study found that m these links can be attractive. The study found that there are significant differences between digital social engineering and hacking of phones and computers..
Entity Configuration for Designing a Port Security Information System: Proposed Extensions of the Vocational Education and Training Curriculum

Port security is one of the most important fields of Vocational Education and Training (VET) maritime studies. In this article, we propose the configuration of entities that are used to design a port security information system for VET education. Our work integrates recent maritime Information Technology (IT) concepts into VET. We record the initial design for building educational software for a school-level security information system that can be used as an extension project for the existing maritime curriculum of VET. This plan, if implemented and completed, will strengthen and expand the boundaries of school knowledge and curriculum. This article describes the design part of the whole project.
Two Layer Image Encryption using Symmetric Key Algorithms

Security of data (text, audio, and images) is becoming more complex with the increment in its amount. In order to upsurge the reliability, the captcha (Completely Automated Public Turing test to tell Computers and Humans Apart) is used to ensure authenticity. In contrast, even these captchas can be hacked and security can be easily impeached, aim of these captchas is to identify if the user is genuine or else if it is just a robot trying to spam the system. This paper presents auxiliary hybridization of AES and Blowfish cryptographic algorithms for image encipherment and decipherment. Here, AES is using Blowfish as its subroutine where Blowfish encrypts and decrypts the AES encoded image. This is then handed to AES for second level decryption. Here the image which is to be encrypted is applied to AES algorithm, its output is further used as an input for Blowfish algorithm. Output of this doubly encrypted image is then decrypted in the reverse order of encipherment. This auxiliary hybridization adds security to the image rendering it the capacity to become useful in highly important organizations. Private key cryptography uses single secret key at both, the sender and the receiver end. Using symmetric key cryptographic algorithm for this process makes the complete process fast and more secure in comparison to when asymmetric cryptographic algorithms are used for the same purpose. Moreover, symmetric key cryptographic algorithms are more suitable for larger files and images. These also help in maintaining the confidentiality of the data.
Time-shared AES-128 implementation with extremely low-cost for smart card applications

Smart cards have seen tremendous growth in the past few years due to their multiple functions delivering ability. They can be used for personal identification, healthcare applications, financial applications, etc. Smart cards contain an embedded circuit that stores and processes a large amount of data. One of the key function performed by the circuit is the cryptographic operation namely encryption. Since these devices are resource constrained, low-cost implementations of cryptographic algorithms are desirable. Advanced encryption standard (AES) is one of the standard encryption algorithm proposed by NIST and is proved to be a suitable candidate for secure and lightweight implementations on hardware compared to its other symmetric counterparts. This work proposes a novel low-cost implementation of AES-128 algorithm using time-shared architectures for contactless smart card applications. The proposed architecture reuses the primitives in a twofold mechanism leading to a novel resource efficient architecture on an FPGA platform.
ANÁLISE DO NÍVEL DE COMPAIXÃO DOS PROFISSIONAIS DE ENFERMAGEM EM TEMPOS DE PANDEMIA

In this sense, this study aims to analyze the compassion of nursing professionals in times of pandemic.An integrative literature review research was carried out, using scientific publications made available in the LILACS, Medline and BDENF databases, which were searched through the Health Sciences Descriptors (DeCS) which were analyzed in a paired way, some aspects as a methodology and level of scientific evidence, with a final sample of 15 articles.The results show that the related factors point out that compassion generates fatigue due to such situations, such as: working conditions, emotions, psychological factors and their sociodemographic characteristics.The presence of exposure to compassion fatigue can lead to various physical and mental illnesses, but it also causes a decline in commitment to work, resulting in a drop in enthusiasm, low efficiency and even negligence.
A Case Study of Applying Rigorous Testing in Practice

This paper reports on experiences and preliminary results we obtained through a case study, in which we applied a rigorous testing method, namely statistical testing based on a Markov chain usage model, to a real-world testing problem in an industrial setting.Although model-based statistical testing has been around for more than two decades with well-established theory and engineering practices, it remains problem-and application-specific to develop a workable testing solution and framework that enables automatic test case generation-execution-evaluation, to provide meaningful and quantifiable statistics/data to make informed management decisions, and to support software certification.We describe the challenge involved in testing an Interactive Voice Response (IVR) module, and demonstrate our approach to tackle the problem following statistical testing practices, from usage modeling all the way to the test case analysis.
Inferring the level of visibility from hazy images

In our research, we would like to exploit crowdsourced photos from social media to create low-cost fire disaster sensors. The main problem is to analyse how hazy the environment looks like. Therefore, we provide a brief survey of methods dealing with visibility level of hazy images. The methods are divided into two categories: single-image approach and learning-based approach. The survey begins with discussing single image approach. This approach is represented by visibility metric based on contrast-to-noise ratio (CNR) and similarity index between hazy image and its dehazing image. This is followed by a survey of learning-based approach using two contrast approaches that is: 1) based on theoretical foundation of transmission light, combining with the depth image using new deep learning method; 2) based on black-box method by employing convolutional neural networks (CNN) on hazy images.
Importance of Research Into Big Data With Machine Learning Approach

This chapter provides some background information, highlights the motivations and problems resolved, and then discusses the aims and contributions of the research conducted. Over the past decades, there has been an explosion in the volume, variety, and velocity of data. Offering effective solutions as a resolution of some major problems this explosion brings has become ever more important. One such solution is big data machine learning (ML) classification or clustering. However, with the solutions offered, we are faced with several problems that include but are not limited to the context.
Broker-based mechanism for cloud provider selection

Cloud computing has recently emerged as a new computing paradigm for delivering on demand virtualised computing resources over the internet on a pay-as-use basis. Applications hosted in cloud have different requirements which include both low level (resource) requirements and high level (performance) requirements. However, most of the cloud providers satisfy SLAs based on resource requirements rather than providing performance guarantees to applications. This gap creates a need for selecting a more suitable cloud provider who can satisfy performance requirements of applications along with resource requirements. This work aims at proposing a broker-based approach to rank cloud providers based on QoS requirements of customers. It helps the SaaS providers to save cost and complexity in choosing a suitable cloud provider for hosting applications. The experimental results show that proposed approach selects the suitable cloud provider for hosting various types of applications satisfying the needs of different cloud customers.
Dimensionality Reduction for Classification of Filipino Text Documents based on Improved Bayesian Vectorization Technique

Dimensionality reduction of feature vector size plays a vital role in enhancing the text processing capabilities to reduce the size of the feature vector used in the mining tasks to achieve a higher classification accuracy.While dimensionality reduction for text classification is becoming a great area of research in most languages, Filipino documents have received little or no attention from researchers.Thus, this paper addresses the issue of dimensionality reduction in representing relevant data from Filipino texts using an improved Bayesian vectorization technique.To validate the effectiveness of improved Bayesian vectorization, the model was compared to the Term Frequency and Inverse Document Frequency (TF-IDF) method.The outcomes are presented using standard measures such as precision, recall, f-score, and accuracy.The results revealed that the improved Bayesian vectorization has significantly better results having 98% classification accuracy compared to 76% classification accuracy of the TF-IDF vectorization technique.
Welcome

editorial Free Access Share on Welcome Authors: Sherif G. Aly The American University in Cairo, Egypt The American University in Cairo, EgyptView Profile , Mohamed Mokbel Qatar Computing Research Institute, HBKU, Doha, Qatar Qatar Computing Research Institute, HBKU, Doha, QatarView Profile , Moustafa Youssef American University in Cairo and Alexandria University, Egypt American University in Cairo and Alexandria University, EgyptView Profile Authors Info & Claims Communications of the ACMVolume 64Issue 4April 2021 pp 42–44https://doi.org/10.1145/3447754Online:22 March 2021Publication History 0citation1,678DownloadsMetricsTotal Citations0Total Downloads1,678Last 12 Months398Last 6 weeks15 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteView all FormatsPDF
Problems of development of a cloud-oriented educational environment of the university

This article discusses the problems of ever-increasing demands on the organization and quality of the educational process on the part of society. Today there are new opportunities for the comprehensive development of students of the XXI century, new, more effective information and communication technologies (ICT), in particular cloud- oriented learning environments (COLE), are developing rapidly. The problems of the development of theoretical and methodological foundations for designing a cloud-oriented educational environment of the university and the justification of the structural scheme of its interaction with the methodological center of the ministry based on the use of cloud technologies are analyzed. It is necessary to introduce such models of the learning environment, which will allow to fully satisfy the demands of teaching staff on the organization and conduct of classes of a new type, the activation of educational activities of students, the formation of digital competence and the comprehensive development of personality. Such opportunities are provided by the use of a cloud-based educational environment of the university.
Evoked Potential Detection using LMS Adaptive Wiener Filter and Wavelet Transform

Signal Processing utilizes scientific investigation and calculations to separate data concealed in signal got from different types of sensors. The Biomedical Signals are defiled by commotion and artifacts. In numerous applications, the ideal signal is not accessible or recognizable straightforwardly. The signal assessment issue is to recuperate in the most ideal manner conceivable, the ideal signal from its debased copy. When obtaining EEG (Electroencephalogram) evoked potentials from scalp electrodes, background activity and other noise is added to the signal. The Wavelet Transform system of estimation surpasses the SNR(Signal to Noise Ratio) by a huge value in just about one sweep of EP(Evoked Potential). The two diverse wavelet Transform systems, Daubechies wavelet transform and Biorthogonal wavelet transform have been discussed in this paper to improve SNR.
Detection of Blast Cells in Microscopic Images Using Optimization Algorithms

Now a day’s in medical field, the most prevalent and hazardous disease is blood cancer. It starts in bone marrow where the blood is produced and prevents many of its regular functions. At an approximation for every three minutes one person in the world is diagnosed with the blood cancer. Early detection of the cancer is necessary for the proper treatment, so as to save the lives of mankind. In general the blood cancer diagnosis will be performed by visual examination of the blood samples of the patient under microscope. The blood cancer detection accuracy of this method depends on the technical skilling abilities of the operator and often leads non-standardized report. To improve patient diagnosis various image processing methods are developed to extract useful information from microscopic images. This could help Hematologists in their diagnostic process. In this paper pre-processing and post-processing methods are applied on microscopic images. These images will be acquired from either public or private database. In this work the images were collected from Microscopyu which is a public database. Pre-processing methods involves color conversion i.e. RGB to grayscale, removal of noise by median filter and an improved contrast enhancement technique CLAHE is implemented. Later Post-processing methods are applied. In this stage Otsu segmentation and optimization algorithms are combined for improving segmentation accuracy. Optimization algorithms used are Particle Swarm optimization (PSO) and Cuckoo Search algorithms (CSO) and Finally features of the segmented image can be extracted from d Scale Invariant Feature Transform (SIFT) . In this work existing method is PSO and proposed method is CSO. At the end the qualitative analysis of the work is done through the statistical parameters like segmentation accuracy, sensitivity, specificity, PSNR and CPU time.
Building a New University at the Intersection of Liberal Arts and Engineering

She is a member of the Association of Professional Engineers and Geoscientists of BC.Her expertise lies in the area of multiphase reaction engineering
THE ROLE OF COMPUTER SCIENCE IN ORGANIZATION OF EDUCATIONAL PROCESS AT UNIVERSITIES USING COMPUTER TECHNOLOGY.

In this article highlights of the design of projects like webpages or websites by students demanding strong background knowledge and diligent work with various literary, artistic and other resources to find and choose the necessary material has a specific place in students teaching.
Assessment of Cybercrime Governance in Ethiopia Since 2004

Communication technology is a recent phenomenon that links countries of the world together.Like other countries of the world Ethiopia also interconnected to global net work via internet technology and committed to expansion of the technology at home to substantiate its economic, social and political advancement goal.However, as a result of digitalization effort at home, the country becomes both source and target of cyber crime.Hence, in order to curb cyber crime, the government of the country engaged in to various activities and this work assess the initiatives under taken by Ethiopian government in the area of cybercrime governance.To do so, the research employs qualitative research methods and secondary source of data.To discharge its global responsibility and prevent itself from cyber crime, Ethiopian government works hard and undertakes various measures.Hence, the government begins its work of fighting cyber crime for the first time by initiating criminal code in 2004 that penalize limited cyber crime in the country.As such, the first initiatives followed by scattered legislations which cover limited area of cyber crime like Telecom fraud offense legislation, National payment system proclamation and recently computer crime proclamation.Similarly, the government also initiates policy measures like ICT policy and strategy, National information security policy and Criminal justice policy.To implement these policies and legislations the government also establishes various institutions.However, these all legislations and policy initiatives are inadequate in cyber crime governance in Ethiopia, due to failure of government to couple its unilateral effort and commitment of fighting cyber crime with transnational cooperation and capacity building.Hence, there is no meaning full and continues capacity building undertaken by Ethiopian government.As a result, there is gap of knowledge and human resource in the country related to cyberspace which in turn creates fertile ground for cyber crime.Ethiopian government also does not engaged into comprehensive and functional transnational cooperation and dormant to be party to any regional and international cyber crime convention.Thus, its domestic effort to fight cyber crime become less significant since cyber crime is borderless.Therefore, in order to successfully defense cyber crime, Ethiopian government should complement its domestic initiative by continues capacity building and transnational cooperation.On the other hand, legislated cyber crime in Ethiopia also infringes freedom of expression and privacy right of peoples.Thus, government should work hard to ensure compatibility within international human right law and cyber crime law as much as possible.
The 9&lt;sup&gt;th&lt;/sup&gt; Symposium of the 88&lt;sup&gt;th&lt;/sup&gt; Academic Annual Congress of the Japan Society of the Hygiene: Various View Points of World Views

Behavioral changes induced by several abused drugs.Behavioral changes have been observed, which are depended on neurotransmitter release using the generalization test for evaluation of drug discriminaltion using mouse behavior.In addition, the development of neurotransmitter selective agonists and antagonists have been used as tools to lead the hypothesis.Recently, manipulation for neuronal activation by optogenetical technique such as Designer Receptors Exclusively Activated by Designer Drug (DREADD) system allows for better understanding for the underlying mechanisms of neuronal circuit.Using such advanced technologies by manipulating speci c neural cells in the brain, it has been discussed which type of the new insight, especially for neuronal system could be gained.The present study was designed to study such as discriminative stimulus The 9 th Symposium of the 88 th Academic Annual Congress of the Japan Society of the Hygiene conclusions about similar datasets.
Crow Search Algorithm (CSA)

Researchers’ are taking keen interest in Optimization algorithms due to their heuristic and meta-heuristic nature. Heuristic algorithms find the arrangement by utilizing the experimentation strategy. Then again, meta-heuristic algorithms discover the response at a more elevated tier. Several nature-based metaheuristic algorithms are easily accessible. Askarzadeh has introduced the Crow search algorithm and stated that it is meta-heuristic optimization algorithm. The astute conduct of the crow moves CSA. Crows are keen on putting away the abundance nourishment at concealing spots and recuperating it at whatever point it is needed. CSA's previous outcomes show that it can unravel different complex building related optimization issues. There are six compelled building plan issues, and CSA is utilized to upgrade these issues. This paper focuses on a far-reaching investigation of CSA in the diverse application is given with the examination just as the exhibitions of the CSA in the different structure is talked about.
A Predictive Classification Method for Email Phishing Attacks u sing Random Forest and A R trees

Concrete and steel structures influences the construction of multi-storey structures. The aid of progressive collapse increases when there is a failure of one or more load bearing structural elements. Thereafter, this case study is carried out to determine the prospective of the progressive collapse of an irregular (L shaped) building due to the failure or removal of two adjacent columns at a time present in the ground floor. Failure may occur because of the natural or manmade accidental loads like explosion or seismic loads, collision of vehicles, etc. Columns at different locations were removed and the slab loads had been increased as per the General Services Administration (GSA) guidelines and the results in terms of Demand Capacity Ratios (DCR) are compared for all the cases. The Demand to Capacity Ratios were calculated for the interested columns. It is observed that when the interior columns were removed then the possibility of progressive collapse is more. This study has been made for the case or earthquake forces for corresponding zone II and zone V.Cyber-attacks are the attempts made by an individual or an organization deliberately, to breach the information system mainly computers of another individual or organization. These attacks have risen in recent years due to various reasons posing the need for systems that can use adaptive learning techniques to detect and mitigate these attacks at an early stage. Phishing is one of the significant cyber-attacks. According to global security report 2019, phishing was the major cause of attacks in corporate networks. Phishing attack uses disguised email to achieve its goal. In this attack, attacker masquerade himself as a trusted individual or a company and trick the email recipient into clicking malicious links or attachments. The proposed method provides a testbed for detecting and mitigating various types of phishing attacks. Machine learning techniques are used to build an intelligent system which can detect phishing attacks. This application uses random forest algorithm with AR-Trees (acceptance-rejection tree algorithm) to determine the attacks by considering various datasets available online and new datasets dynamically constructed for making the system ready to mitigate future phishing attacks.