The Right to life its comprehensive protection from Conception.

Janneth X. Iglesias; Milton Jiménez; M. E. Machado; Ximena Cangas

doi:https://doi.org/10.54216/JSPR.010204

International Journal of Neutrosophic Science | 2023

The General Exponential form of a Symbolic Plithogenic Complex Numbers

In this study, we defined a symbolic plithogenic complex number's general exponential form. A symbolic plithogenic complex number's general trigonometric form was defined. Theories have been supported by evidence showing how to find the general exponential form's conjugate for symbolic plithogenic complex numbers, division for symbolic plithogenic complex numbers, multiplication for two symbolic plithogenic complex numbers, and inversion for symbolic plithogenic complex numbers.

groups

Yaser Ahmad Alhasan mail -

Raja Abdullah Abdulfatah mail -

Suliman Sheen mail

link https://doi.org/10.54216/IJNS.220309

Volume & Issue

Vol. Volume 22 / Iss. Issue 3

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International Journal of Neutrosophic Science | 2023

Analyzing the United Nations Speeches with a Neutrosophic Approach to Text Mining in The Context of Türkiye’s Foreign Policy

Document clustering is an integral and important part of text mining.  In case of classical clustering, data item belongs to only one cluster, whereas in Plithogenic approach to fuzzy clustering, data point may fall into more than one cluster. Thus, Plithogenic approach fuzzy clustering leads to wherein each data point is associated with more than one membership function that expresses the degree to which individual data points belong to the cluster. Additionally, his speeches at the UN will be analyzed with a neutrosphic approach. With the help of this approaches, in this study, speeches of the UN sessions attended by Turkish diplomats in the United Nations (UN) will be analyzed to understand the priorities of the country in international politics, the change and continuity in these policies. The texts of the UN sessions attended by Turkish diplomats between 2015 and 2023 were taken as data set. Such a large volume of data was analyzed with the help of text mining. For this purpose, each year's data was analyzed separately using word frequencies and clustering analysis, and then topic modeling was performed for each year's data using the Latent Dirichlet Allocation (LDA) method.

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Muhammet Musa Budak mail -

Mehmet Fatih Sert mail -

Ilker Yasin Durmaz mail

link https://doi.org/10.54216/IJNS.220310

Volume & Issue

Vol. Volume 22 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2023

Utilizing Neutrosophic Logic in a Hybrid CNN-GRU Framework for Driver Drowsiness Level Detection with Dynamic Spatio-Temporal Analysis Based on Eye Aspect Ratio

Driver drowsiness has been identified as a major cause of roadway accidents globally. Efficiently determining the extent of drowsiness can greatly enhance preventive measures. This study proposes a novel approach, combining convolutional neural networks (CNN) and Gated Recurrent Units (GRU) to dynamically evaluate both the presence of drowsiness and its severity based on the Eye Aspect Ratio (EAR). By bridging spatial features extracted by CNNs with temporal sequences through GRU, our model offers a robust and real-time assessment of drowsiness levels, paving the way for enhanced safety measures in vehicular systems. Incorporating Neutrosophic Logic enables a more robust representation of uncertainty and ambiguity in the data and enhances the accuracy of driver drowsiness level detection within the Hybrid CNN-GRU framework. The model’s hybrid CNN-GRU structure combines CNN layers to extract spatial information from Human eye Images and GRU units to represent temporal correlations between frames. In-car cameras and sensors must be integrated to implement the suggested system in real-time and enable continuous driver behavior monitoring. The system alerts early warnings and takes action when drowsiness is detected, lowering the likelihood of accidents caused by weary drivers. The CNN-GRU hybrid architecture accurately detects fatigue during real-time driving. Performance metrics, including accuracy, recall, and F1-score, are provided for comparative research utilizing baseline models. Model behavior may be understood by visualizing tiredness detection and carefully examining false positives and negatives. The proposed CNN-GRU framework outperforms traditional methods such as SVM, KNN, and BPNN by achieving a significantly higher accuracy of 99.5%. It increases the recognition of driver tiredness by proposing a trustworthy and adaptable hybrid CNN-GRU deep learning system. This project is implemented in Python; it offers a practical and versatile solution for real-time driver drowsiness level detection. The proposed technology has the potential to dramatically increase traffic safety by sending out early warnings and taking steps to lessen the risks related to driver fatigue.

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Abdel-Haleem Abdel-Aty mail -

Ahmed A. H. Abdellatif mail -

Kottakkaran Sooppy Nisar mail -

Shankar Rao Munjam mail -

Rasha M. Abd El-Aziz mail -

Ahmed I. Taloba mail

link https://doi.org/10.54216/IJNS.220212

Volume & Issue

Vol. Volume 22 / Iss. Issue 2

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Journal of Intelligent Systems and Internet of Things | 2023

An Ensemble Learning Approach for detection of Chronic Kidney Disease (CKD)

Chronic kidney disease (CKD) is a common and possibly fatal condition affecting billions worldwide. Early detection and accurate diagnosis of CKD are critical for timely intervention and improved patient outcomes. In recent years, machine learning techniques have shown great promise in assisting medical professionals in detecting and diagnosing various diseases. This study aims to develop a novel machine learning (ML) model for detecting CKD using clinical and demographic data. The dataset used in this study comprises a comprehensive collection of patient records, including laboratory test results, medical history, and demographic information. Feature selection is one of the techniques that, combined with the ML approach, select the significant features. Several ML algorithms were implemented to detect CKD in the early stages but identified the issues with existing ML algorithms. The developed models' performance is assessed using precision, accuracy, and recall metrics. Additionally, feature importance analysis is conducted to identify the key factors influencing CKD diagnosis. The strength of the proposed approach shows accurately by identifying the individuals at risk of CKD and distinguishing between different stages of the disease. The dataset used for this research was collected from the UCI repository, which consists of 25 attributes, 550 samples, 400 CKD affected, and 150 standard models. The dataset consists of two folders, training and testing. The training utilizes 1000 samples with detailed patient health conditions. The developed CKD detection model shows promising results, achieving high accuracy of 97.98%. on the test dataset. By leveraging machine learning algorithms, this approach can assist healthcare professionals in making more informed decisions regarding early intervention and personalized treatment plans for patients with CKD. Ultimately, applying machine learning techniques in CKD detection can improve patient outcomes and reduce healthcare costs.

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B. Narasimha Swamy mail -

Rajeswari Nakka mail -

Aditi Sharma mail -

S. Phani Praveen mail -

Venkata Nagaraju Thatha mail -

Kumar Gautam mail

link https://doi.org/10.54216/JISIoT.100204

Volume & Issue

Vol. Volume 10 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2023

Ambient air pollution monitoring and health studies using low-cost Internet-of-things (IoT) monitor within KNUST Community

Urban environments with high industrialization are infested with hazardous chemicals and airborne pollutants. These pollutants CO, O3, SO2, NO2, and PM can have devastating effects on human health, causing both acute and chronic diseases such as respiratory infections, lung cancer, and heart disease. Air pollution monitoring is vital to warn citizens of the health risks associated with exposure to high concentrations of these criteria pollutants. This study designed a low-cost IoT monitor to measure concentration levels of criteria pollutants emitted from transportation sources within Kwame Nkrumah University of Science and Technology environs. Three monitoring sites, KNUST Tech junction, Ayeduase gate junction and KNUST campus junction, were identified as the locations within the proximity of the university for the deployment of the monitor. Hourly and mean daily CO, NO2, O3 and SO2 concentrations at each of the three sites were measured for a week using the IoT monitor, when students were in school and when students were on vacation. The average daily CO, NO2 and O3 concentrations measured at the selected locations when school was in session and during vacation were presented on histogram. The mean weekly concentrations of CO, NO2 and O3 were also estimated as 13.2ppm, 0.277ppm and 0.106ppb respectively at KNUST Tech junction; 10.1ppm, 0.254ppm and 0.110ppb respectively at Ayeduase gate junction; and 8.0ppm, 0.415ppm and 0.100ppb respectively at the KNUST campus junction when school was in session. The results show that the concentrations of all the pollutants were higher and exceeded the EPA standards except for CO at KNUST Campus junction monitoring site. These high levels of emissions are an indication of a health concern for the students at the university and university authorities can device means of curbing it.

groups

Benjamin Afotey mail -

Christina Lovely-Quao mail

link https://doi.org/10.54216/JISIoT.100205

Volume & Issue

Vol. Volume 10 / Iss. Issue 2

Details open_in_new

Journal of Social Problems Research | 2022

Monitoring of graduates: employment possibilities, skills and functions of Lawyers (UNIANDES Ibarra)

The aim was to describe the employment possibilities of graduates in the UNIANDES Ibarra Law course, their competences and functions, for which theoretical positions were used that address follow-up programs for graduates in higher education, the analysis of their competences and their impact on labor markets. Descriptive field research was applied, with a quantitative approach, the sample was integrated by 122 legal professionals and the questionnaire was used as an instrument, and descriptive statistics complemented with qualitative analysis allowed interpreting the data. The findings indicate that the surveyed law professionals have the skills required to start their work projects, however, they have faced limitations that prevent them from achieving sustained development, this information should be used by the University and by the State to join efforts and redefining its policies with the goal of satisfying the training and employability demands of legal professionals  

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Diego Chamorro Valencia mail -

Teresa de Jesús Molina G. mail -

Lenin Horacio Burbano G. mail -

Alipio A. Cadena Posso mail

link https://doi.org/10.54216/JSPR.010202

Volume & Issue

Vol. Volume 1 / Iss. Issue 2

Details open_in_new

Journal of Social Problems Research | 2022

Shifting the Burden of Proof Regarding the Absence of Unjustified Dismissal in Ecuador

In the workplace the worker is considered the weakest part of the employment relationship and untimely dismissal is a social problem in Ecuador, for which compensation has been determined in the legal regulations, provided that it has been voluntarily recognized or proven in a legal proceeding, the plaintiff (ex-worker) being the party required to prove that assertion, which is complicated given the circumstances in which a dismissal is made. Hence, the objective in this paper was to determine who should correspond in a legal process to prove the existence or not of an untimely dismissal. Theoretical and empirical methods were used, the results of which in the city of Santo Domingo showed that of the cases resolved in 2017, 89% could not prove the existence of untimely dismissal and the surveys carried out by legal professionals. 90% said that there should be a reversal of burden of proof to the employer to prove the inexistence of untimely dismissal. Based on this, it was concluded that it is necessary to implement the reversal of the burden of proof on the inexistence of untimely dismissal in order to strengthen and allow workers to have fair access to their compensations and benefits, preventing the employer from taking advantage of them of the difficulty and limited evidence that the former worker has at his disposal at the time of termination of employment in an untimely manner.

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Cacpata C. Wilson Alfredo mail -

Gil Betancourt Antonella Stefanía mail -

Enríquez G. Nicole Jazmín mail -

Castillo N. Katherine Trinidad mail

link https://doi.org/10.54216/JSPR.010203

Volume & Issue

Vol. Volume 1 / Iss. Issue 2

Details open_in_new

Fusion: Practice and Applications | 2023

Deep Neural Network-based Reversible Image Steganography Technique using Circle-U-Net

Data communication is made at the ease with the advent of the latest communications medium and tools. The concern over data breaches has increased. The digital media communicated across the network are susceptible to unapproved access. Though numerous image steganography approaches were existing for concealing the secret image into the cover image there are still limitations such as inadequate restoration of image quality and less embedding capacity. To overwhelm such shortcomings recently many image steganography approaches based on deep learning are proposed. In this work, a Circle-U-Net-based reversible image steganography technique is proposed. The model includes a contracting process, which includes residual bottleneck as well as circle connect layers which obtain context; an expanding process, which includes sampling layers as well as merging layers for pixel-wise localization. The reversible image steganography (RIS) is carried out with neural network models such as CNN, U-Net scheme, and Circle-U-Net structure on TinyImageNet-200 and Alzheimer’s MRI dataset. The proposed technique is experimented along with RIS using CNN and RIS using U-Net. The experimental results depict that the RIS using the Circle-U-Net structure performs better among the three models.

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N. Malarvizhi mail -

R. Priya mail -

R. Bhavani mail

link https://doi.org/10.54216/FPA.130210

Volume & Issue

Vol. Volume 13 / Iss. Issue 2

Details open_in_new

Fusion: Practice and Applications | 2023

Mutual authenticated key agreement in Wireless Infrastructure-less network by Chaotic Maps based Diffie-Helman Property

Because wireless infrastructure-less networks are dynamic, varied, and scattered, implementing security in them is exceedingly difficult. Authentication is the most crucial prerequisite for security deployment. It is difficult to implement security based on public-key infrastructure with centralized third-party authentication in an environment without infrastructure. We build and test a chaotic map-based technique that handles authentication as one of the key qualities to accomplish security. We allocate the key management responsibility to cluster-heads after dividing the infrastructure-less into several clusters with cluster-heads. The Diffie-Helman property, which is based on Chebyshev polynomials, is used in the proposed work to establish authentication. Our suggested method avoids unnecessary computations like modular exponentiation and elliptical curve scalar multiplications. It also ensures that the secret session-key is only established between the two designated entities and is resistant to a variety of network attacks.

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D. Neela M. Shyam mail -

Mohammed Ali Hussain mail

link https://doi.org/10.54216/FPA.130211

Volume & Issue

Vol. Volume 13 / Iss. Issue 2

Details open_in_new

Journal of Social Problems Research | 2022

The Right to life its comprehensive protection from Conception.

Humanity has struggled for its conservation over time, from the conception stage the child girl has had a primordial attention, so nowadays she has been subjected to several sociological and ethical studies about the legal interruption of life in Latin American countries in recent years has introduced to their legislation the possibility of decriminalizing abortion, so justifying that the termination of pregnancy is not threatening life because the product that is in the womb is a fetus not considered yet person, from when a human being is considered to have life or since when is its origin ?, Some scholars indicate from its conception others since its birth, but the most successful is that life is formed from its conception, has its rights recognized in treaties and international conventions, Constitution of the Republic, organic laws, ordinary laws. The objective of the research is to identify the legal contradiction that exists in the bills of the decriminalization of abortion and the constitutional norm that protects the right to life from its conception. The research carried out was based on the application of logical historical methods, inductive deductive, synthetic analytical, having as objective the present, to determine if legally the project presented to decriminalize abortion in Ecuador is consistent with the Ecuadorian constitutional norm.

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Janneth X. Iglesias Quintana mail -

Milton Jiménez Montenegro mail -

M. E. Machado Maliza mail -

Ximena Cangas Oña mail

link https://doi.org/10.54216/JSPR.010204

Volume & Issue

Vol. Volume 1 / Iss. Issue 2

Details open_in_new