Energy Aware Scheme for Underwater Wireless Sensor Networks

Heba M.; Muna M.; Noor Q.; Zinah O.

doi:https://doi.org/10.54216/IJWAC.050101

International Journal of Neutrosophic Science | 2022

Neutrosophic cognitive maps for analysis of social problems analysis

Investors have been flocking to the information technology (IT) industry recently. Any commercial or IT company's success is directly proportional to its employees' efforts. The workforce's contributions are crucial when it comes to the success of technology or any other business on the global stage. However, they will disregard their personal and social lives to achieve their aim. Workers in the private sector, particularly those in the information technology industry, suffer from mental health issues such as stress, depression, anxiety, and addiction. Using Neutrosophic Cognitive Maps (NCM), we evaluated the daily problem they face. The NCM decision-making system incorporates iterative tasks of resolving conflicts until the optimal answer is reached. The NCM uses neutrosophic graphs to model depending on the opinions of experts. Studying the issue with such vague data calls for an approach such as this, which eschews the use of statistics. For unlabeled data, NCM is the most effective method.

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V. B. Frantz Dimitri mail -

M. G. Teresa De Jesús mail -

P. A. Edmundo Enrique mail

link https://doi.org/10.54216/IJNS.190129

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

Fusion: Practice and Applications | 2022

Multi-Sensor Data Fusion for Target Tracking Using Machine Learning Techniques

Target detection using multi fusion data is one of the common techniques used in military as well as defence units. The usage of a wide variety of sensors is now possible due to modern data fusion technology. The major problem is the existing multi-sensor fusion technique is loss of data and delay is message transfer. To overcome the existing problems, proposed work includes optimization, machine learning, and soft computing techniques. Multi Sensor Data Fusion (MSDF) is becoming an increasingly significant field of study and is being explored by a broad range of individuals. Data defects, outliers, misleading data, conflicting data, and data association are some data fusion concerns. In addition to the statistical advantages of more independent observations, the precision of an observation may be improved by using a variety of different types of sensors. Target tracking has earned a lot of attention in recent years in the realm of surveillance and measurement systems, particularly those in which the state of a target is approximated based on measurements. Academics as well as implementers in the fields of radar, sonar, and satellite surveillance are interested in the bearings-only tracking (BOT) problem. The BOT is the sole option available in many surveillance systems, such as those found aboard submarines. Significant difficulties arise because of the constrained observability of target states based only on bearing measurements. The work that is suggested tackles the limitations of EKF and its derivatives in controlling MSDF within the context of BOT. Specifically, the study identifies divergence as a primary challenge and works to devise solutions for it. It is recommended that two key methods of fusion, data level and feature level (or state level), be investigated in depth. This is in recognition of the fact that the MSDF may increase observability, thereby reducing the tendency of the tracking algorithm to diverge and realizing a better estimate of the states. The Information Filter, which is a casting of the Kalman Filter, and its expansions are employed via extensive simulation to lessen the influence of initial assumptions on the convergence of MSDF tracking algorithms. This is accomplished by using the Kalman Filter.

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A. Audumbar Pise mail -

Radhika Kapshikar mail

link https://doi.org/10.54216/FPA.080205

Volume & Issue

Vol. Volume 8 / Iss. Issue 2

Details open_in_new

International Journal of Neutrosophic Science | 2022

The NILPOTENT Characterization of the finite neutrosophic p-groups

A well known and referenced global result is the nilpotent characterisation of the finite p-groups. This undoubtedly transends into neutrosophy. Hence, this fact of the neutrosophic nilpotent p-groups is worth critical studying and comprehensive analysis. The nilpotent characterisation depicts that there exists a derived series (Lower Central) which must terminate at {ϵ} ( an identity ) , after a finite number of steps. Now, Suppose that G(I) is a neutrosophic p-group of class at least m ≥ 3. We show in this paper that Lm−1(G(I)) is abelian and hence G(I) possesses a characteristic abelian neutrosophic subgroup which is not supposed to be contained in Z(G(I)). Furthermore, If L3(G(I)) = 1 such that pm is the highest order of an element of G(I)/L2(G(I)) (where G(I) is any neutrosophic p-group) then no element of L2(G(I)) has an order higher than pm.

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S. A. Adebisi mail -

Florentin Smarandache mail

link https://doi.org/10.54216/IJNS.190134

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2022

The Representation of Refined Neutrosophic Matrices By Refined Neutrosophic Linear Functions

The aim of this paper is to solve the problem of representing refined neutrosophic matrices by linear functions, where it describes the structure of refined neutrosophic linear transformations that represent refined neutrosophic matrices. On the other hand, this work introduces a novel algorithm to compute a basis of any refined neutrosophic vector space depending on the classical basis of its corresponding classical vector space.

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Mohammad Abobala mail -

M. Bisher Ziena mail -

R. Iqbal Doewes mail -

Zahraa Hussein mail

link https://doi.org/10.54216/IJNS.190131

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2022

Neutrosophic TOPSIS for prioritization Social Responsibility Projects

Social responsibility is the most important thing to consider while working on a project. When deciding on a project or taking part in a bid, it is crucial to understand the nature and potential consequences of the risks involved. Attempting to implement projects with cutting-edge technologies appears to be necessary, necessitating up-to-date and continuous planning to implement the relevant matters in light of the ever-increasing growth of urban communities, the need to carry out tasks, and the rising standard of living. Due to the strong demand, these strategies try to improve quality while decreasing prices. In the beginning, Smarandache suggests using neutrosophic sets. These sets are an improvement above traditional fuzzy set theory in reflecting the uncertainty and fuzziness of real-world issues. Three decision-making states are considered: uncertainty, truthiness, and falseness. The fuzzy set degree in Zadeh's classic theory is merely the membership function. On the other hand, three membership functions are considered in a neutrosophic setting. An indeterminacy degree is considered, which is not the case with intuitionistic fuzzy sets. To express decision makers' perspectives on the truthiness (T), falsity (F), and indeterminacy (I) for a fuzzy set concurrently, this paper expands the usual neutrosophic TOPSIS approach to interval-valued neutrosophic. One example of how the suggested strategy might be put to use is to prioritize initiatives in the realm of corporate social responsibility using a combination of expert opinion and objective criteria.

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S. Alvarez Hernandez mail -

P. P. Jairo Mauricio mail -

L. Vázquez Maikel mail

link https://doi.org/10.54216/IJNS.190132

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2022

Interval-Valued Neutrosophic Deductive Systems of Hilbert Algebras

Interval-valued neutrosophic sets (IVNSs) are a notion that was initially developed by Wang et al.19 The idea of IVNSs to deductive systems (DSs) in Hilbert algebras is presented in this study. It is shown how intervalvalued neutrosophic deductive systems (IVNDSs) relate to their level cuts. In addition, certain related features are examined as well as the homomorphic inverse image of IVNDSs in Hilbert algebras.

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Aiyared Iampan mail -

P. Jayaraman mail -

S. D. Sudha mail -

Said Broumi mail -

N. Rajesh mail

link https://doi.org/10.54216/IJNS.190133

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2022

Social sports Competition Scoring System Design Using Single Value Neutrosophic Environment

The goal of this work the critical criteria that affect social sports competition organization's arrangement. Then determine the relations between criteria with others and alternatives. So, the evaluation of the process of social sports competition contains many conflict criteria. The multi-criteria decision-making (MCDM) process is an effective tool for dealing with conflict and complex criteria. This work employs a new integrated model for dealing with the problem in an analytical hierarchal process (AHP) and Vi&scaron;ekriterijumsko Kompromisno Rangiranje (VIKOR) methods under single-valued neutrosophic sets (SVNSs). SVNSs are the best tool for overcoming uncertainty and incomplete information. The AHP method is used for computing the weights of criteria then VIKOR is used for rank alternatives. The twelve criteria and five alternatives are used in this problem. An illustrative example is provided to present a robust hybrid model. This paper can help organizations and countries for arrangement and organize social sports completion with a scoring system design.

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D. M. Ramírez Guerra mail -

Y. M. Gordo Gómez mail -

L. J. Cevallos Torres mail -

F. G. Palacios Ortiz mail

link https://doi.org/10.54216/IJNS.190135

Volume & Issue

Vol. Volume 19 / Iss. Issue 1

Details open_in_new

Journal of Cybersecurity and Information Management | 2022

Re-Evaluating the Necessity of Third-Party Antivirus Software on Windows Operating System

There is a general assumption that one must purchase costly antivirus software products to defend one’s computer system. However, if one is using the Windows Operating System, the question that arises is whether one needs to purchase antivirus software or not. The Windows operating system has a market share of 31.15% behind Android with a market share of 41.56% worldwide amongst all the operating systems. This makes Windows a prime target for hacking due to its large user base. Windows 11 a recent upgrade to the Windows operating system has claimed to have taken its security to the next level. There is a need to evaluate the capability of the Windows 11 default security against antivirus evasion tools. This research investigated the capability of Windows 11 default security by evaluating it against 6 free and open-source antivirus evasion tools: TheFatRat, Venom, Paygen, Defeat Defender, Inflate and Defender Disabler. The criteria for the selection of the antivirus evasion tools were free and open source and recently updated. A research lab was set up using Oracle VirtualBox where two guest machines were installed: a Windows 11 victim machine and the Kali Linux attacking machine. The antivirus evasion tools were installed on the Kali Linux machine one at a time to generate a malware and pass it to the victim machine. Apache web server was used in holding the malicious sample for the Windows 11 victim machine to download. A score of 2 was awarded to an antivirus evasion tool that successfully evaded the Windows 11 security and created a reverse connection with the attacking machine. From the research results: TheFatRat had a 25% evasion score, Venom had 20% while the rest had a 0% evasion score. None of the payloads generated with the antivirus evasion tools was able to create a connection with the Kali Linux attacking machine. The research results imply that the default Windows 11 security is good enough to stand on its own. A third-party antivirus solution will only supplement the already good protection capability of Windows 11.

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Faisal A. Garba mail -

Rosemary M. Dima mail -

A. Balarabe Isa mail -

A. Abdulrazaq Bello mail -

A. Sarki Aliyu mail -

F. Umar Yarima mail -

S. Abbas Ibrahim mail

link https://doi.org/10.54216/JCIM.090105

Volume & Issue

Vol. Volume 10 / Iss. Issue 1

Details open_in_new

Journal of Cybersecurity and Information Management | 2022

Machine Learning-based Information Security Model for Botnet Detection

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet detection for information security. For effectual recognition of botnets, the proposed model involves data pre-processing at the initial stage. Besides, the model is utilized for the identification and classification of botnets that exist in the network. In order to optimally adjust the SVM parameters, the DFA is utilized and consequently resulting in enhanced outcomes. The presented model has the ability in accomplishing improved botnet detection performance. A wide-ranging experimental analysis is performed and the results are inspected under several aspects. The experimental results indicated the efficiency of our model over existing methods.

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Heba M. Fadhil mail -

Noor Q. Makhool mail -

Muna M. Hummady mail -

Zinah O. Dawood mail

link https://doi.org/10.54216/JCIM.090106

Volume & Issue

Vol. Volume 9 / Iss. Issue 1

Details open_in_new

International Journal of Wireless and Ad Hoc Communication | 2022

Energy Aware Scheme for Underwater Wireless Sensor Networks

The development of wireless sensor networks (WSNs) in the underwater environment leads to underwater WSN (UWSN). It has severe impact over the research field due to its extensive and real-time applications. However effective execution of underwater WSNs undergoes several problems. The main concern in the UWSN is sensor nodes’ energy depletion issue. Energy saving and maintaining quality of service (QoS) becomes highly essential for UWASN because of necessity of QoS application and confined sensor nodes (SNs). To overcome this problem, numerous prevailing methods like adaptive data forwarding techniques, QoS-based congestion control approaches, and various methods have been devised with maximum throughput and minimum network lifespan. This study introduces a novel Seeker Optimization based Energy Aware Clustering Scheme for Underwater Wireless Sensor Networks (SOEACS-UWN). The presented SOEACS-UWN model follows the operation on a collection of solutions named search population (i.e., human team) and considered optimization procedure as a searching process of optimum solutions via human teams. The SOEACS-UWN model constructs a fitness function for effectual CH choices using diverse variables namely distance, residual energy, node degree, centrality, and link quality. The simulation analysis of the SOEACS-UWN model is tested and the outcomes were investigated under diverse aspects. The experimental outcomes demonstrated the supremacy of the SOEACS-UWN model over other approaches.

groups

Heba M. Fadhil mail -

Muna M. Hummady mail -

Noor Q. Makhool mail -

Zinah O. Dawood mail

link https://doi.org/10.54216/IJWAC.050101

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

Details open_in_new