Usage Of Models Research Articles

Feature selection algorithm for usability engineering: a nature inspired approach

AbstractSoftware usability is usually used in reference to the hierarchical software usability model by researchers and is an important aspect of user experience and software quality. Thus, evaluation of software usability is an essential parameter for managing and regulating a software. However, it has been difficult to establish a precise evaluation method for this problem. A large number of usability factors have been suggested by many researchers, each covering a set of different factors to increase the degree of user friendliness of a software. Therefore, the selection of the correct determining features is of paramount importance. This paper proposes an innovative metaheuristic algorithm for the selection of most important features in a hierarchical software model. A hierarchy-based usability model is an exhaustive interpretation of the factors, attributes, and its characteristics in a software at different levels. This paper proposes a modified version of grey wolf optimisation algorithm (GWO) termed as modified grey wolf optimization (MGWO) algorithm. The mechanism of this algorithm is based on the hunting mechanism of wolves in nature. The algorithm chooses a number of features which are then applied to software development life cycle models for finding out the best among them. The outcome of this application is also compared with the conventional grey wolf optimization algorithm (GWO), modified binary bat algorithm (MBBAT), modified whale optimization algorithm (MWOA), and modified moth flame optimization (MMFO). The results show that MGWO surpasses all the other relevant optimizers in terms of accuracy and produces a lesser number of attributes equal to 8 as compared to 9 in MMFO and 12 in MBBAT and 19 in MWOA.

Experimental investigation and prediction of compressive strength of high-strength concrete containing waste ceramic powder using gene expression programming

The high volume of carbon dioxide produced in cement plants and the feasibility of reusing waste materials from factories in recent years has become one of the main concerns of research centers and environmental associations. Therefore, the main purpose of this research is to evaluate the feasibility of reusing waste materials with a focus on waste ceramic powder (WCP), as a semi-active aluminosilicate material that can be replaced as a percentage of cement used in concrete. WCP, in addition to activating the potential of using a waste material in concrete, can also reduce cement consumption. Therefore, in this research, cement replacement percentages between 0 and 50% in three water to cement ratios of 0.3, 0.4 and 0.5 in 24 concrete mixtures have been used to perform compressive strength tests. In order to provide a usable computational model, the gene expression programming (GEP) method has been used to predict the compressive strength of the samples. The results of experimental research indicate that in the ratio of water to cement 0.3 at the age of 90 days, the sample containing 20% of WCP has reached a compressive strength of 72.57 MPa. This result is almost equal to the control sample and therefore the use of this percentage is recommended for this ratio of water to cementitious materials. Finally, the results indicate the very good performance of the GEP method by increasing the number of chromosomes and increasing the correlation coefficient between experimental and numerical data up to 98%. Therefore, the GEP method has a significant advantage over other methods by providing an analytical relationship and high accuracy.

Ad Hoc Vehicle Networks: Recapitulation and Challenges

Being ad-hoc in design, VA NET is a form of networks generated by the idea of building up a network of cars for a specific needs or circumstance. In addition to the benefits, VANET poses a large number of challenges such as providing QoS, high bandwidth and connectivity, and vehicle and individual privacy security. Each report discusses VANET 's state-of-the-art, explaining the relevant problems. We address in depth network design, signal modelling and propagation mechanisms m, usability modeling, routing protocols and network security. The paper's key results are that an effective and stable VANET satisfies all architecture criteria such as QoS, minimal latency, low BER and high PDR. At the end of the paper are addressed several primary work areas and challenges at VANET.

Usability Evaluation and User Acceptance of Mobile Applications for Saudi Autistic Children

<p class="Body">The evolution of mobile technologies in learning, has been increased the requirements for developing appropriate usability model to fall into the same line with mobile learning applications. Usability of mobile learning applications is a topic that is into research, this paper focuses a tailored designed model called (M-UTUAT) mobile usability model that combines People at the Centre of Mobile Application Development (PACMAD) and the unified theory of acceptance and use of technology (UTAUT) to form a more robust model. As an addition to the usability research, an application (ICT) was developed for children with speech delays and children diagnosed with autism spectrum. The application is a mobile/tablet-based application that developed according to mobile usability measures to get the maximum learning skills and abilities to help autistic children. It has been designed according to the needs of the children specific to their category and skills. The autism spectrum is a broad spectrum with high and low disabilities. The application consists of both visual and audio aids to help children feel comfortable and associate objects more easily with their original meaning and connections. (PECS) is one of the most common techniques that have been clinically proven to be effective in such cases. This application helped an individual with autism spectrum as well as children with speech delays or disabilities to communicate and correlate faster and easily. The application can help so many families by constructing a more communicative path for people with disabilities. The application is innovative that it developed in the Arabic language to serve Arabic learners as most of the autistic applications available serve English learners. Results gathered after questionnaire highlight the usability issues with the (ICT) application. We developed an app to overcome usability issues.</p>

Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

Digital and intelligent buildings are critical to realizing efficient building energy operations and a smart grid. With the increasing digitalization of processes throughout the life cycle of buildings, data exchanged between stakeholders and between building systems have grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent and hinders the development of energy-oriented applications that can be reused across buildings, limiting the scalability of innovative solutions. Addressing this challenge, our review paper systematically reviews metadata schemas and ontologies that are at the foundation of semantic interoperability necessary to move toward improved building energy operations. The review finds 40 schemas that span different phases of the building life cycle, most of which cover commercial building operations and, in particular, control and monitoring systems. The paper’s deeper review and analysis of five popular schemas identify several gaps in their ability to fully facilitate the work of a building modeler attempting to support three use cases: energy audits, automated fault detection and diagnosis, and optimal control. Our findings demonstrate that building modelers focused on energy use cases will find it difficult, labor intensive, and costly to create, sustain, and use semantic models with existing ontologies. This underscores the significant work still to be done to enable interoperable, usable, and maintainable building models. We make three recommendations for future work by the building modeling and energy communities: a centralized repository with a search engine for relevant schemas, the development of more use cases, and better harmonization and standardization of schemas in collaboration with industry to facilitate their adoption by stakeholders addressing varied energy-focused use cases.

Evaluating PSAU Mobile Application Based on People at the Center of Mobile Application Development (PACMAD) Usability Model: Empirical Investigation

This study investigates the extent to which the usability attributes, namely, effectiveness, efficiency; learnability and memorability, satisfaction, errors, and cognitive load of PSAU mobile application exist from students’ point of view who were enrolling at the academic year 2019-2020 in College of Business Administration (CBA) at Prince Sattam Bin Abdulaziz University. The study employs the People at the Center of Mobile Application Development (PAMCAD) usability model to determine the extent to which the usability attributes are available of PSAU mobile application. A survey-based methodology is used to collect data from a random sample size of 137 enrolled students in the College of Business Administration (CBA) at Prince Sattam bin Abdulaziz University. The results demonstrate the state of usability attributes of PSAU mobile application is acceptable; the highest mean was 3.3 for the cognitive load dimension, after that, the learnability and memorability dimensions with mean 3.0. The lowest mean is 2.4 for the Efficiency dimension. The overall mean for usability is 2.8 which reflect the level of usability for the PSAU mobile application. The results of this study should be useful to IT deanships and related policymakers at the university level with empirical evidence about the issues and problems that faced users of mobile applications in higher educational institutions in KSA; and helping in developing high-quality mobile application.

Scientometric Data and Open Access Publication Policies of Clinical Allergy and Immunology Journals.

IntroductionThe scientific merit of a paper and its ability to reach broader audiences is essential for scientific impact. Thus, scientific merit measurements are made by scientometric indexes, and journals are increasingly using published papers as open access (OA). In this study, we present the scientometric data for journals published in clinical allergy and immunology and compare the scientometric data of journals in terms of their all-OA and hybrid-OA publication policies.MethodsData were obtained from Clarivate Analytics InCites, Scimago Journal & Country Rank, and journal websites. A total of 35 journals were evaluated for bibliometric data, journal impact factor (JIF), scientific journal ranking (SJR), Eigenfactor score (ES), and Hirsch index (h-index). US dollars (USD) were used for the requested article publishing charge (APC).ResultsThe most common publication policy was hybrid-OA (n = 20). The median OA publishing APC was 3000 USD. Hybrid-OA journals charged a higher APC than all-OA journals (3570 USD vs. 675 USD, p = 0.0001). Very strong positive correlations were observed between SJR and JIF and between ES and h-index. All the journals in the h-index and ES first quartiles were hybrid-OA journals.ConclusionBased on these results, we recommend the use of SJR and ES together to evaluate journals in clinical allergy and immunology. Although there is a wide APC gap between all-OA and hybrid-OA journals, all journals within the first quartiles for h-index and ES were hybrid-OA. Our results conflict with the literature stating that the OA publication model's usage causes an increase in citation counts.

Estimation of parameters for a humidity-dependent compartmental model of the COVID-19 outbreak.

Building an effective and highly usable epidemiology model presents two main challenges: finding the appropriate, realistic enough model that takes into account complex biological, social and environmental parameters and efficiently estimating the parameter values with which the model can accurately match the available outbreak data, provide useful projections. The reproduction number of the novel coronavirus (SARS-CoV-2) has been found to vary over time, potentially being influenced by a multitude of factors such as varying control strategies, changes in public awareness and reaction or, as a recent study suggests, sensitivity to temperature or humidity changes. To take into consideration these constantly evolving factors, the paper introduces a time dynamic, humidity-dependent SEIR-type extended epidemiological model with range-defined parameters. Using primarily the historical data of the outbreak from Northern and Southern Italy and with the help of stochastic global optimization algorithms, we are able to determine a model parameter estimation that provides a high-quality fit to the data. The time-dependent contact rate showed a quick drop to a value slightly below 2. Applying the model for the COVID-19 outbreak in the northern region of Italy, we obtained parameters that suggest a slower shrinkage of the contact rate to a value slightly above 4. These findings indicate that model fitting and validation, even on a limited amount of available data, can provide useful insights and projections, uncover aspects that upon improvement might help mitigate the disease spreading.

Machine Learning Use for Prognostic Purposes in Multiple Sclerosis.

The course of multiple sclerosis begins with a relapsing-remitting phase, which evolves into a secondarily progressive form over an extremely variable period, depending on many factors, each with a subtle influence. To date, no prognostic factors or risk score have been validated to predict disease course in single individuals. This is increasingly frustrating, since several treatments can prevent relapses and slow progression, even for a long time, although the possible adverse effects are relevant, in particular for the more effective drugs. An early prediction of disease course would allow differentiation of the treatment based on the expected aggressiveness of the disease, reserving high-impact therapies for patients at greater risk. To increase prognostic capacity, approaches based on machine learning (ML) algorithms are being attempted, given the failure of other approaches. Here we review recent studies that have used clinical data, alone or with other types of data, to derive prognostic models. Several algorithms that have been used and compared are described. Although no study has proposed a clinically usable model, knowledge is building up and in the future strong tools are likely to emerge.

Application of imiquimod-induced murine psoriasis model in evaluating interleukin-17A antagonist

BackgroundInterleukin-17A (IL17A) is a proinflammatory cytokine critically involved in autoimmune diseases, and monoclonal antibodies of IL17A have been approved for clinical treatment of psoriasis. However, a usable psoriatic animal model has been always required for preclinical evaluation of IL17A antagonists. Imiquimod (IMQ)-induced psoriasis model is widely used in fundamental research, but it’s not able to accurately show anti-psoriatic effect of IL17A antagonists with conventional modelling condition.ResultsOn female C57BL/6 mice, with optimization on the usage of IMQ, positive control reagent and anti-mIL17A antibody, a 7-day model with proper testing window, acceptable disease severity as well as high repeatability was developed, and the efficacy of IL17A antagonist can be objectively evaluated by several qualitative and quantitative indices. Meanwhile, we validated the detailed involvement of IL17A signaling in disease progression, confirmed that the expression levels of IL17A and its related cytokines were induced by IMQ application, and its downstream cytokines can be inhibited by IL17A antagonist treatment. In further study, we revealed that IL17A was transient induced by IMQ and directly caused downstream signaling activation. This finding on the kinetical change of IL17A signaling will manifest the pharmacokinetics-pharmacodynamics investigation of IL17A antagonists.ConclusionsOur work presents the application of a convenient psoriatic animal model in the research and development of IL17A antagonists, meanwhile providing extra evidence for understanding IL17A’s role in the progression of IMQ-induced psoriasis model, which manifest the research and development of IL17A antagonists.

Chronic ciprofloxacin and atrazine co-exposure aggravates locomotor and exploratory deficits in non-target detritivore speckled cockroach (Nauphoeta cinerea).

The global detection of ciprofloxacin and atrazine in soil is linked to intensive anthropogenic activities in agriculture and inadvertent discharge of industrial wastes to the environment. Nauphoeta cinerea is a terrestrial insect with cosmopolitan distribution and great environmental function. The current study probed the neurobehavioral and cellular responses of N. cinerea singly and jointly exposed to atrazine (1.0 and 0.5μgg-1 feed) and ciprofloxacin (0.5 and 0.25μgg-1 feed) for 63days. Results demonstrated that the reductions in the body rotation, maximum speed, turn angle, path efficiency, distance traveled, episodes, and time of mobility induced by atrazine or ciprofloxacin per se was exacerbated in the co-exposure group. The altered exploratory and locomotor in insects singly and jointly exposed to ciprofloxacin and atrazine were verified by track plots and heat maps. Furthermore, we observed a decrease in acetylcholinesterase and anti-oxidative enzyme activities with concomitant elevation in the levels of lipid peroxidation, nitric oxide, and reactive oxygen and nitrogen species were significantly intensified in the midgut, hemolymph, and head of insects co-exposed to ciprofloxacin and atrazine. In conclusion, exposure to binary mixtures of ciprofloxacin and atrazine elicited greater locomotor and exploratory deficits than upon exposure to the individual compound by inhibiting acetylcholinesterase activity and induction of oxido-inflammatory stress responses in the insects. N. cinerea may be a usable model insect for checking contaminants of ecological risks.

CNN based watermarking technique for authentication of valid subscribers

The use of Watermarking has become very important technique for security and authentication and also many more as we are that plays a important role in providing very good security and authentication for image transmission and also in the reception, In the case of broadcasting and general transmission of confidential secret information. The deep learning techniques with multiple layers having multiple waits. The deep learning techniques are adding Intelligence (AI) to the existing models, In the recent past it has presented great success proficiencies for number of tasks, like visual investigation, speech detection, natural language processing and etc. In this process there have come up many usable models. Building up a creation level profound learning structure is a non-insignificant assignment, which requisites a lot of preparing information, amazing processing assets, and human algorithmic. Therefore, it is a very importance which can actually harm human exploration. Ill-conceived recreating, conveyance, and the induction of exclusive profound learning models can prompt copyright encroachment and it is financial mischief to demonstrate makers. Hence, it is vital for devises method to ensure the licensed innovation of profound learning model.

Adaptive Thresholds of EEG Brain Signals for IoT Devices Authentication

In this paper, a new authentication method has been proposed for the Internet of Things (IoT) devices. This method is based on electroencephalography EEG signals, and hand gestures. The proposed EEG signals authentication method used a low price NeuroSky MindWave headset. This was based on choosing the adaptive thresholds of attention and meditation mode for the authentication key. Hand gestures to control authentication processes by using a general camera. To verify that a new authentication method is widely accepted, it must meet two main conditions, security and usability. The evaluation of the prototype usability was based on ISO 9241-11:2018 standards usability model. Results revealed that the proposed method demonstrated the usability of authentication by using EEG signals with the accuracy of 92%, the efficiency of 93%, and user satisfaction is acceptable and satisfying. To evaluate the security of the prototype, we consider the most important three threats related to IoT devices which they are guessing, physical observation, and targeted impersonation. The results showed that the password strength, using the proposed system is stronger than the traditional keyboard. The proposed authentication method also is resistant to target impersonation and physical observation.

Finansijska analiza kao deo izveštavanja finansijskog menadžmenta proistekla iz preporuka interne revizije u preduzećima

Financial analysis is part of the overall reporting, primarily financial management, and then top management in companies. The initiative to initiate financial analysis can come from the following parts of the broader management function of the company: internal controls, internal audits, top management, external audits, government agencies, shareholders, business owners and others. In this paper, the authors paid special attention to the importance of the initiative that originated from the company's internal auditors. In addition, the authors point out the importance of shaping and creating the very basis of financial analysis in companies in order to make a usable model of the proper functioning of reporting to the top management of a large number of companies. The aim of this paper is to show the advantages of properly setting up a financial management reporting system. In addition, proper top management reporting can contribute to creating better business results in the company.

On-Air Hand-Drawn Doodles for IoT Devices Authentication During COVID-19

In this paper, a new natural human interaction authentication method is proposed for Internet of Things (IoT) devices. In this method, the user draws a doodle on the air for authentication. On-air drawing refers to virtually drawing free hand-drawn doodle passwords through hand gestures on the air without touching anything that is recommended during COVID-19. This study uses the Google Quick Draw Doodle dataset for password doodles. The proposed method is based on a typical video camera, two lightweight convolutional neural networks (CNNs) and a Kalman filter. The first CNN for hand gesture classification was used to overcome dynamic hand gesture challenges on the air. Second CNN for authentication verification. A Kalman filter was used to correct and smooth the path drawn on the air. Two main goals must be achieved to accept the new authentication method: usability and security. The usability evaluation was based on the ISO 9241-11:2018 standard usability model. The results revealed that the accuracy of the proposed authentication method was 95%, efficiency was 94%, and user satisfaction was acceptable. The evaluation of security was based on two threats related to IoT devices: guessing and physical observation. The results show that the password strength of the proposed authentication method is stronger than the traditional 4-digits PIN password. The proposed authentication method is also resistant to physical observation threats.

Intrusion detection system using deep learning methodologies

Intrusion Detection Systems (IDS) are the backbone that helps secure organizations and individuals from malicious internet traffic. Deep-Learning is another field of computer science that enables us to build productive Artificial Intelligence (AI) models that can be applied in a variety of fields. In this paper, we discuss the CSE-CIC-IDS2018 dataset for internet intrusion detection and provide a detailed study and analysis of various deep learning approaches that could be used to make a secure intrusion detection system. We test the accuracy of these algorithms and their effectiveness in detecting the malicious traffic for multiclass classification of the traffic in 14 different classes including benign traffic and malicious traffic. The outcome of which is to obtain a model framework based upon deep learning to build a usable model for an intelligent IDS that could potentially be used for real time data traffic security.

Development of the African Killifish as a New Model to Study Aging and Suspended animation

We have pioneered a new model organism for aging research, the naturally short-lived African killifish Nothobranchius furzeri. The African killifish lives in ephemeral pools of water in Africa, and has evolved a short life cycle adapted to this habitat. Its embryos can also resist drought until the next wet season in a state of ‘suspended life’. In laboratory conditions, the African killifish has a maximal lifespan of about 4-6 months, and is, so far, the shortest-lived vertebrate that can be bred in captivity. We have successfully transformed this natural short-lived vertebrate into a usable model organism for aging research, including de novo assembly of the genome and CRISPR-Cas9 mediated genome-editing. Our goal is to use this model to discover new principles underlying aging, longevity, and ‘suspended animation’ in vertebrates.

Design Build and Analyze of Website Usability of Campus Publishing Agency

Introducing a product certainly requires a medium or intermediary so that the product can be known by the wider community. One of the most frequently used media nowadays is the website or marketing site. The main purpose of this website is to promote products that have been made based on the works of the authors to be better known to the wider community. A website must also be user-friendly, easy to understand, access, remember, and provide useful information to its users. The creation of this website uses the Web Development Life Cycle (WDLC) method, the website will be tested using the usability model which is a qualitative analysis to determine how easy the user is using the interface of an application. The data collection techniques will use the interview technique, with the determination of the sample with purposive sampling technique. The Data obtained later will be analyzed and tested validity with techniques found in qualitative research methods.

DEFECTIVE ENDOSPERM-D1 (Dee-D1) is crucial for endosperm development in hexaploid wheat

Hexaploid wheat (Triticum aestivum L.) is a natural allopolyploid and provides a usable model system to better understand the genetic mechanisms that underlie allopolyploid speciation through the hybrid genome doubling. Here we aimed to identify the contribution of chromosome 1D in the development and evolution of hexaploid wheat. We identified and mapped a novel DEFECTIVE ENDOSPERM–D1 (Dee-D1) locus on 1DL that is involved in the genetic control of endosperm development. The absence of Dee-D1 leads to non-viable grains in distant crosses and alters grain shape, which negatively affects grain number and thousand-grain weight. Dee-D1 can be classified as speciation locus with a positive effect on the function of genes which are involved in endosperm development in hybrid genomes. The presence of Dee-D1 is necessary for the normal development of endosperm, and thus play an important role in the evolution and improvement of grain yield in hexaploid wheat.

Cross-Platform Usability Model Evaluation

It is becoming common for several devices to be utilised together to access and manipulate shared information spaces and migrate tasks between devices. Despite the increased worldwide use of cross-platform services, there is limited research into how cross-platform service usability can be assessed. This paper presents a novel cross-platform usability model. The model employs the think-aloud protocol, observations, and questionnaires to reveal cross-platform usability problems. Two Likert scales were developed for measuring overall user satisfaction of cross-platform usability and user satisfaction with the seamlessness of the transition between one device and another. The paper further employs a series of objective measures for the proposed model. The viability and performance of the model were examined in the context of evaluating three cross-platform services across three devices. The results demonstrate that the model is a valuable method for assessing and quantifying cross-platform usability. The findings were thoroughly analysed and discussed, and subsequently used to refine the model. The model was also evaluated by eight user experience experts and seven out of the eight agreed that it is useful.