Reviewerly/exHarmony huggingface dataset:
Improving Cyber Defense Education Through National Standard Alignment

There has been a fast-growing demand for cybersecurity professionals to defend cyber space and information systems. With more and more programs and course offerings in cybersecurity popping up in higher education, it is important to have a consistent and reliable quality standard to guide and evaluate the training and preparation of qualified cyber defense workforce. The national Centers of Academic Excellence in Cyber Defense Education (CAE-CDE) designation program jointly sponsored by the US National Security Agency (NSA) and Department of Homeland Security (DHS) is a rigorous national standard with specific criteria for maintaining the quality of cybersecurity education. This article explains the CAE-CDE program criteria and requirements and discusses the important role of the special designation in improving cyber defense education and workforce development. This article illustrates the educational value and quality impact of the CAE-CDE program with three case studies: (1) University of Missouri – St. Louis; (2) American Public University; and (3) Robert Morris University.
Research on Face Expression Recognition

Face Expression Recognition (FER) has become main area of interest due to its wide applications. Automatic Facial expression recognition has drawn the attention of researchers as it has many applications. Facial Expression Recognition gives important information about emotions of a human being. Many feature selection methods have been developed for identification of expressions from still images and real time videos. This work gives a detailed review of research works done in the field of facial expression identification and various methodologies implemented for facial expression recognition.
Fractional Rider and Multi-Kernel-Based Spherical SVM for Low Resolution Face Recognition

Face recognition is a unique feature for recognizing the individual in the biometric system and is advantageous since face recognition is a non-contact process.However, biometric recognition is ineffective due to the low-resolution images, wanting the need for the effective recognition system.Accordingly, this research concentrates on developing an effective face recognition strategy using low and high-resolution images.Initially, the input low-resolution images are preprocessed for enhancing the image contrast and subjected to the generation of the high-resolution image.Then, the feature extraction using the GWTM process presents the texture features that facilitate effective recognition using the spherical Support Vector Machine (SVM) that works using the multiple kernel function.In the GWTM process, proposed fractional-ROA is engaged in the optimal fusion of the features acquired from the wavelet, Linear Binary Patterns (LBP), and Gabor filter.The analysis of the recognition method is initiated based on the metrics, such as False Alarm Rate (FAR), False Rejection Ratio (FRR), and accuracy.The proposed fractional-ROA-based face recognition acquires the maximal accuracy, and minimal FRR and FAR of 0.98, 0.0123, and 0.0017, respectively.
Evaluation of the Relative Tectonic Activity of the Adıyaman fault within the Arabian-Anatolian.

The left-lateral strike-slip Adıyaman fault is located in eastern Turkey within the plate boundary deformation zone between Arabia and Anatolia.The Adıyaman fault is a major splay from the East Anatolian Fault (EAF), one of the most important tectonic structures in the Eastern Mediterranean region.These faults are consequence of the collision between the Arabian and Anatolian plates and the resulting westward tectonic escape of Anatolia.Although the EAF has been intensively studied since its discovery in the late 1960s, little is known about the Adıyaman fault and its tectonic activity.In this study, we extract geomorphic indices including mountain-front sinuosity (S mf ), valley floor width-to-height ratio (V f ), stream length-gradient (S L ), catchment Asymmetry Factor (AF) and hypsometric integrals and curves (HI and HC) to evaluate the relative tectonic activity of the Adıyaman fault.These three geomorphic indices (AF, HI, and HC) are averaged to define an index for Relative Tectonic Activity (RTA) that allows the Adıyaman fault to be divided into categories of low, moderate and high RTA.The results confirm that the Adıyaman fault is an active fault with high to moderate Quaternary tectonic activity.However, this fault is of minor importance on accommodating plate boundary deformation, as evidenced by the recent crustal motions determined by GPS studies.Nevertheless, it is worthwhile to note that the Adıyaman fault still poses a significant seismic hazard for the region despite its relatively moderate tectonic activity.
Syllogistic logic with “Most”

Abstract We add Most X are Y to the syllogistic logic of All X are Y and Some X are Y . We prove soundness, completeness, and decidability in polynomial time. Our logic has infinitely many rules, and we prove that this is unavoidable.
Smartphone enabled Counterfeit Note Detection using Siamese Network

Counterfeit note has a disastrous impact on a country’s economy. The circulation of such fake notes not only diminishes the value of genuine note but also results in inflation. The feasible solution to this burning issue is to create awareness about the counterfeit notes among public and to equip them with a technology to detect fake notes on their own. Though there exist numerous research articles on detection of fake notes, they are not handy. The reason for this could be the unavailability or unaffordability in acquiring the equipment for the same. This paper proposes an approach whose implementation can easily be deployed on a smart phone and hence anyone with access to them can use the application to detect the fake notes. The proposed approach consists of the processing phases including image procurement, pre-processing, data augmentation, feature extraction and classification. ₹500 notes are considered for experimentation analysis. Out of 17 distinctive features, 3 such from the obverse side are considered to evaluate the genuineness of the note. Siamese neural network is employed to build a model for effective classification of the notes. The performance of the proposed approach is evaluated at 85% with respect to accuracy.
A Multilevel Thresholding Approach Based on Improved Particle Swarm Optimization for Color Image Segmentation

In this paper, a hybrid Otsu and improved Particle Swarm Optimization (PSO) algorithm is presented to deal with multilevel color image thresholding problem, named APSOW. In APSOW, the historical information represented by the local best solutions found so far by PSO population are permuted among the current population, using a randomized greedy process. APSOW also implements a weedout operator to prune the worst individuals from the population. The proposed APSOW is compared to other hybrid EAs and Otsu approaches from literature (include standard PSO model) through twelve benchmark color image problems, showing its potential and robustness.
An Unsharp Masking Algorithm Embedded With Bilateral Filter System for Enhancement of Aerial Photographs

Human visual system is more sensitive to edges and ridges in the images which composed of high spatial frequency components. Digital images having more spatial variations may contain informative content than their counterparts. Remote sensing images are one of those categories covering different aspects of land surface variations, aerial photographs are obtained on board image sensors on flying platform. Aerial photographs represent the land surfaces consists of textural and structural objects make more presence of edges. Interpolating information of aerial photographs become clumsy when the pixels are corrupted with noises at different density of levels. The kind of aerialphotographsare acquired in various way such as multi/hyper spectral sensors on board of satellites or the planes, by synthetic aperture radar (SAR) in remote sensing. The intelligence of the aerial photographs affected because of noises during image formation process and atmospheric factors. In this paper, unsharp masking (USM) algorithm based image denoising framework is proposed with Gaussian and bilateral filters. Structure similarity index(SSIM) and Image enhancement factor (IEF) based performance comparisons were studied for various noises on aerial photographs and the experimental results shown that the bilateral filter with USM system outperforms the Gaussian filter with USM. The simulation setup demonstrated using both additive and multiplicative noises with the different levels of noise density on aerial photographs.
Blockchain Technology in India – Challenges and Opportunities

The Blockchain is a distributed database of all transactions or digital events that is maintained as Blocks. These transaction records that are executed between parties are stored as blocks in Blockchain and shared among parties that maintain the blocks. Each Block is analyzed, verified and stored by the parties who are part of the network/system. Each block contains the details of a single transaction and a hash key of the previous block. Digital Crypto Currency and Bitcoin use Blockchain as its backbone. By design, Blockchains are much secured and the technology ensures flawless record keeping. The Crypto Currency, Bitcoin which is used as a decentralized digital currency shall be transacted peer-to-peer without any third party involvement. Other areas like financial transactions, identity management, food traceability, medical records, even election processes shall be secured using Blockchain. Electronic payments have made a major breakthrough in Indian banking sector and continue to grow with more innovations in the enhancements to the existing system. Slowly Electronic payments are replacing paper based transactions which saves time and cost. Volume of transactions has also increased with more transparency and the sector is showcasing good progress. Introduction of Bitcoin and crypto currencies in Finance and Banking sectors have brought in a paradigm shift on the fundamental transaction processes of this sector. Essential elements of trade, ownership and trust are ensured through Blockchain which makes a disruptive intervention on whole transaction management model. Constructive and critical exploration of this technology in the context of India will bring out more prospective on how this technology shall be leveraged. This paper will present the current state of Blockchain adoption in India and will cover the challenges and opportunities in this space..
Quadruple Factors Interference and Its Effects on Quality of Outsourcing Testing: A Case Study

The share of IT companies in the global market has been increasing and many organizations are moving to outsource their software development projects to off-shore vendors. Recently, the IT sector in Palestine has been gaining much ground with many software development companies specializing in software development outsourcing services. Maintaining high-quality and robust software products has always been a key success factor in the outsourcing sector. Software testing is considered to be the main phase in which teams can assure high quality of software products.Therefore, we did an exploratory multiple-case study and this study involvesfour Palestinian software outsourcing companiesof different domain. We provide insights about factors that affect the quality of software testing practice, and explore applied testing techniques, methods and confronted challenges. The results reveal that there is big attention toward software testing assoftware development companies are investing more effort, time, and technical resources into their quality assurance teams. Additionally, among the applied software testing methods, more attention needs to be directed towards test automation. Moreover, more theoretical and technical courses targeting software quality assurance should be included in national Palestinian universities’ curriculum. Finally, we propose a new model that can help practitioners to enhance the quality of their outsourced software products
FPGA Implementation of RECTANGLE Block Cipher Architectures

In recent time, various lightweight algorithms have been proposed to provide security in a constrained resource environment. With so many algorithms and their different implementations, it is hard to choose the appropriate security primitive for an application. In this work, various hardware implementations of lightweight block cipher RECTANGLE is proposed like Iterative design, 16-bits architecture, Reduced Substitution box design, RAM-based design and Iterative design with Partial loop unrolled. These designs provide aid in overcoming the problem of security in a constrained resource environment. Architectures are designed and implemented in various FPGA platforms. Results are extensively evaluated and compared on the basis of throughput, throughput/slice, area utilization, energy requirement and power consumption for their implementation in different FPGA platforms. Best trade-off among throughput and area is given by Iterative design with partial loop unrolling. It also gave best energy consumption values for all FPGAs. Ram-based design utilized least number of registers for its implementation.
LEA 192: High Speed Architecture of Lightweight Block Cipher

High-throughput lightweight cryptography calculation is the need of the present world to convey between two asset obliged devices Pipelining is the technique have been used to achieve high throughput. In this paper we have target to lightweight block cipher LEA. Block size of LEA is 128 and key size 128, 192, and 256 bit. In this paper we have focus on LEA architecture for 192- bit key size and achieve very good throughput. This method has a higher capability of throughput as compared to previous LEA ciphers. Proposed work is 56% improved version of compared paper for respective Speed and area also less than previous architecture. Graph representation have been shown of different matrices and comparison.
Effects of Financial Innovations on the Profitability of Deposit Money Banks in Nigeria

This study examined the effects of financial innovation on the profitability of deposit money banks in Nigeria. the general purpose of the study was to examine the effect of financial innovation on the profitability while the specific objectives was to examine the effect of automated teller machine, electronic fund transfer, internet banking, mobile banking and investment on information communication technology on return on equity of deposit money banks.The study formulated four hypotheses and used panel data regression to analyze the secondary data extracted from the annual reports and accounts of the fourteen firms for the period 2009 to 2017.Return on equity was the dependent variables while automated teller machine, electronic fund transfer, internet banking, mobile banking and investment on information communication technology on return were the independent variables.Findings of the study revealed that automated teller machine and electronic fund transfer have negative relationship with return on equity while internet banking, mobile banking and investment on information communication technology have positive relationship with return on equity.The study recommends that deposit money banks should adopt financial innovations, deposit money banks invest in technological innovations and banks should transform banking service by adapting to mobile banking and agency banking so that not only to providing jobs but also increase market share.
Fraud Triangle Theory: Calling for New Factors

The famous financial scandal of Enron, WorldCom and 1 Malaysia Development Berhad has harmed the auditor’s reputation as the protector of shareholders’ rights. Auditors have done their part by conducting systematic audit procedures and “What Could Go Wrong” analysis in assessing the possible risk area to assist fraud detection in the client’s financial matters. However, fraud cases never seem to decline. Regardless of any safeguarding measures established, fraud incidents can just occur and be worsened by economic downturn and prolonged inflation especially after the pandemic ends. Additionally, the characteristic of the modern business environment, technology sophistication and new generation traits had challenged Cressey Fraud Triangle Theory on its validity and relevancy. Therefore, associating all these possible challenges into consideration, this study aims to review prior literature related to the evolution of Cressey fraud theory to propose a new insight in considering relevant motivation factors that drive fraud penetrations. From the review, the study discovered the need for a detailed evaluation and research on the essential fraud element in constructing an all-rounded fraud prevention mechanism.
A Statistical Application on Determining the Prognostic Factors of Oral Squamous Cell Carcinomas (Oscc) In Malaysia

Oral cancer is an important global health concern, representing the sixth most frequent malignant tumor. The oral squamous cell carcinoma (OSCC) is the most common malignant neoplasm of the oral cavity with up to 50% of mortality rate (highest prevalence being identified in Asia). In 2012, it has been reported that 14.1 million new cancer cases and 8.2 million cancer deaths. Numbers of studies have been performed to investigate the factors that have direct and indirect or both associated with the OSCC, including their survival time. In this paper, the potential clinicopathological prognostic factors will be determined in patients who attended Hospital Universiti Sains Malaysia from 2005 to 2015. For such prediction, the use of hazard regression is used previously, but here an attempt is made to propose a covariate-dependent prognostic model to identify the factors and the predictor importance according to the statistical significant point of view. The proposed model is very useful for the prediction and for the inferences of the patient’s management time with the high-risk clinicopathological factors.
Blockchain and digital transformation of insurance business models

The blockchain has recently received significant attention from researchers and practitioners, highlighting its perceived impact and emerging disruption potential. However, most of the literature on blockchain is dedicated to the banking sector, with limited attention to other sectors and answering how blockchain technology may affect business models. This research examines how the adoption of blockchain technology transforms business model components in the insurance industry. We performed a qualitative research through a multi-case study analysis of three blockchain implementations in the insurance sector. Based on the data, we identified that blockchain technology has the potential to contribute to the digital transformation of business models in all aspects. This research provides insightful implications for blockchain and insurance relevant researchers and executives.
Model-based deployment of secure multi-cloud applications

The wide diffusion of cloud services, offering functionalities in different application domains and addressing different computing and storage needs, opens up the possibility of building multi-cloud applications relying upon heterogeneous services, offered by multiple cloud service providers. This flexibility not only enables an efficient usage of resources, but also allows to cope with specific requirements in terms of security and performance, while requiring, however, a typically high development effort. The MUSA framework leverages a DevOps approach to develop multi-cloud applications with desired Security Service Level Agreements (SSLA). This paper describes the MUSA Deployer models and tools, which aim at decoupling the multi-cloud application modelling and development from application deployment and cloud services provisioning. With MUSA tools, designers and developers are able to express and easily evaluate the application security requirements, and to deploy it automatically by acquiring and configuring cloud services with the needed software components.
Energy efficient resource management techniques in cloud environment for web-based community by machine learning: a survey

Cloud computing is a platform where the services of information technology are delivered by retrieval of resource from the internet through web applications and web tools instead of using direct server. In order to offer better quality of service to the larger number of web-based community users, many companies are adopting cloud computing. A dynamic number of web-based community user are interacting with each other via cloud computing. The number of online users is not just limited to manual counting figure so it is extremely important to manage each and every resource efficiently by minimising the energy consumption. To increase the performance of the system, the concepts of machine learning can be used to solve the challenges occur in cloud computing while managing resources for online communities. In this paper, we discuss the application of machine learning in cloud environment and its effect on web-based community.
Give students ownership of credentials with blockchain technology

When Central New Mexico Community College started looking at digital services for diplomas, transcripts, and other credentials, they were guided by the institution's strategic plan. One of the priorities was to shift from college‐owned to student‐owned technology, said Feng Hou, chief information officer and chief digital learning officer.
Privacy-Utility Tradeoffs in Routing Cryptocurrency over Payment Channel Networks

As the adoption of cryptocurrencies grows to unprecedented levels, the scalability of blockchain technologies has become increasingly important. A major open question is whether cryptocurrencies are fundamentally able to support as much traffic as traditional, centralized solutions. One prominent approach for improving the scalability of blockchains is payment channel networks (PCNs) [1]. Instead of committing every transaction to the blockchain, a separate overlay network (called a PCN) is maintained. Each node represents a user, and each edge (or payment channel) represents pre-allocated funds that can be efficiently transacted between the two endpoints under a mutual agreement. Users can transact with each other by relaying payments over a sequence of channels.
The media effect on individuals in the cultural transformation of Shekhawati Region: a case study

It is seen that media access influences the opinion formation of an individual, affecting their decision making ability in bringing an attitudinal change leading to a social transformation. In India, the technologically driven media has reached rural parts of the country and seems to be greatly influencing the indigenous culture of Lachhmangarh Village of Shekhawati Region, Rajasthan. To understand the extent of cultural transformation, various factors of culture, i.e., food, lifestyle, art and architecture, costume, music, dance, language and festivals are studied. The study attempts to identify the penetration of media and subsequent positive and negative influence on cultural transformation. It also attempts to analyse efforts undertaken by media and government to preserve the culture. The researcher conducted ethnographic study validating it through method triangulation. 200 respondents' filled questionnaires formed the quantitative data while qualitative data was collected through observation method, in-depth interviews and focused group discussion with 50 respondents each.