Call for Participation
We invite you to join us in International Conference on Soft Computing, Data mining andData Science (SCDD 2023)
This conference will provide an excellent international forum for sharing knowledge and resultsin theory, methodology and applications of Soft Computing, Data mining, and Data Science. The
Conference looks for significant contributions to all major fields of the Soft Computing, Datamining, and Data Science in theoretical and practical aspects.
Highlights of SCDD 2023 include:International Conference on Cloud, IoT and Security (CIOS 2023)
International Conference on Computer Science, Engineering and Artificial Intelligence(CSEAI 2023)
International Conference on Speech and NLP (SPNLP 2023)
International Conference on Educational Research (EDUR 2023)

Registration Participants
Non-Author / Co-Author / Simple Participants (no paper)
100 USD (With proceedings)
Here's where you can reach us : scdd@scdd2023.org (or) scddconf@yahoo.com

Accepted Papers
Exploring Sentiment Analysis Research: a Social Media Data Perspective
Zahra Dahish1, 2 and Shah J Miah1, 1Newcastle Business School, College of Human and Social
Futures, University of Newcastle, NSW, Australia, 2Management Information System, College ofBusiness Administration, Jazan University, Saudi Arabia
ABSTRACTBusinesses use sentiment analysis in different ways for generating decision support insights.
Existing sentiment analysis studies related to social media data have been significantly grown but,
its insights and trends were not fully revealed for new researchers in the data mining field.
Therefore, it is of paramount task to delineate the trend holistically for knowledge growth in thefield of the data mining and text analytics research. The study addresses the research gap througha comprehensive bibliometric review of 523 research articles published in the Scopus database(between 2018 and 2022) to discern the content and thematic analysis. We adopt an automatedbibliometric study approach using the R-tool- biblioshiny for generating and presenting
outcomes. Finding points on the vital usages of sentiment analysis such as innovation,transparency, and improved efficiency. It also highlights the uniqueness of sentiment analysis forsynthesizing social media content to examine various aspects such as the knowledge-domain mapthat detects author collaboration networks.
KEYWORDS
Social Media, Sentiment Analysis, Bibliometric Analysis, Systematic literature review .
Teaching and Learning With Ict Tools: Issues and Challenges
Er. Kamaljit Kaur Assistant Professor Department of Computer Science Khalsa College,
Garhdiwala
ABSTRACTThe students nowadays are more friendly with tech devices. So, to make it less boring need tostart innovative ways that involve technology. Teaching via ICT tools have the potential to makea change in the academic sector. It is a dynamic learning method. It provides more benefits ascompared to the traditional blackboard and chalks learning. Due to the rapid progress intechnology, there are many new ways of learning that have started. These methods attract themind of most students. It is interesting and better than the traditional methods in many ways.
These methods spark curiosity in the mind of the students. The whole process of education cansometimes feel tedious for students. In this digital era, ICT use in the classroom is important forgiving students opportunities to learn and apply the required 21st century skills. Hence studying
the issues and challenges related to ICT use in teaching and learning can assist teachers inovercoming the obstacles and become successful technology users. With the advent ofInformation and Communications Technologies (ICT) in education, teachers form their own
beliefs about the role of ICT as a teaching tool, the value of ICT for student learning outcomesand their own personal confidence and competency. Barriers exist in integrating ICT in teaching
and learning. The barriers are extrinsic to the teacher and include lack of resources, time, accessand technical support.
KEYWORDSICT Tools, Teaching and Learning Technology , Issues and Challenges.
Text Generation With Gan Networks Using Feedback Score
Dmitrii Kuznetsov, Department of Software Engineering, South China University of Technology,
Guangzhou, China
ABSTRACT
Text generation using GAN networks is becoming more effective but still requires new
approaches to achieve high-quality output. The usage of a discriminator model in GAN solves
this task partially but it can be extended using more natural ways such as feedback scoring.
Feedback or response is a natural part of conversations and not only consists of words, but also
can take other shapes such as emotions, or other reactions. In dialogue processes feedback is afactor influencing the next phrase or reaction. Depending on this feedback or response we correct
our possible answers by trying to change the tone, context, or even structure of the sentences.
Applying feedback as part of the GAN model structure will give us new ways to apply feedback
and generate well-controlled outputs with defined scores which is very important in real-world
applications and systems. With GAN networks and their instability in training and uniquearchitecture, it becomes trickier and requires new ways of solving this problem. The matter of
feedback usages GAN network we will review in this paper and experiment with 2 different
approaches to applying feedback such as using its score in the GAN discriminator‘s loss function
or integrating score values into generator model layers.
KEYWORDS
Neural Networks, Text generation, GAN networks, Autoencoders, Controlled text generation .
An Illumination Invariant Convolution Module for Zero-shot Object Detection in the Night
Jian Wei, Qinzhao Wang, Zixu Zhao Army Academy of Armored Forces, Beijing 100071, China
ABSTRACTIntelligent detection is an important part of the research of military intelligent technology. When
only daytime training data is available, it is difficult to train a consistent model for object
detection at night. How to eliminate the inconsistent performance resulting from different
illumination conditions is a critical work under resolution. The illumination invariant convolution
module (IIC) based on dynamic learning is proposed, which realizes a cross-domain detection
model that can be trained only in the daytime scene and directly used for target detection in the
low-light scene. It models the conversion relationship between the visible light image and thetarget constant illumination feature map. Experiments show that compared with the model basedon data augmentation and style transformation, the proposed method has a more stable detectionperformance and higher average precision (AP) in the self-built dataset. Furthermore, it gains
consistent performance in the small sub-dataset, as well.
KEYWORDS
Cross-Domain; Illumination Invariant; Object Detection; YOLO.
An Architecture Forreliable Cyber Attack Detection in Iot Networks to Increase theTrustworthiness Between Nodes
Dr.S.Malathi1 and S.Razool Begum2, 1Assistant Professor of Computer Science, Swami
Dayananda College of Arts and Science,Manjakkudi.Tiruvarur(dt),Tamilnadu, India, Affiliated to
Bharathidasan, University, 2Research Scholar, A.VeeriyaVandayar Memorial Sri Pushpam
College(Autonomous), Thanjavur-613503,Tamilnadu, India, Affiliated to Bharathidasan
University
ABSTRACTThe security qualities of IoT trustworthiness are combined with information technology (IT) thatare safety, safety, consistency, flexibility, and privacy. Traditional security tools and procedures
are insufficient to protect IoT platforms because of the differences in protocols, restricted update
options, protocol mismatch, and outdated operatingsystem utilized in the Industrial system. In thispaper, a scalable and reliable cyber-attack identification method to enhance the credibility of an
IoT network (i.e. a supervisory control and data acquisition (SCADA) network). In particular, anensemble-learning model that is a combination of a random subspace (RS) learning approach anda random tree (RT) learning method for identifying cyber-attacks utilizing network traffic fromSCADA-based IoT platforms. The proposed model is unique and it employs industrial protocolbased network traffic where random subspace (RS) resolves the susceptibility of unnecessary
characteristics,and ensemble random tree (RT) to minimize the overfitting issue, resulting in a
detection engine based on industrial protocols with better detection rates.
KEYWORDS
Cyber-attack, traffic, protocol, random subspace, random tree, SCADA, and ensemble approach.
Iot Enabled Human Health Monitoring System
Aryaa, Deepak Kumar, Harsh Sharma, Aditi Saini, Pravin Kaushik, Dept. of Electronic andCommunication Engineering KIET Group of Institution Ghaziabad, India
ABSTRACTThe goal of this paper is to develop a human health monitoring system (HHMS) that aids inearlier diagnosis of a human being and monitoring following recovery. The concept uses a
combination of two subsystems which monitors the human health parameters such astemperature, SpO2, Heart Rate, ECG, and also the environment parameters such as temperatureand humidity. The human characteristics are extracted using a variety of sensors, and the data isthen analysed on a mobile application subsystem through an Internet of Things (IoT) subsystem.
Findings have successfully proven using the HHMS prototype to constantly measure body

temperature, heart rate, SpO2, ECG, and surrounding temperature and humidity. Our mobile
application evaluates how reliable the method is for tracking these metrics.
KEYWORDS
IoT, Health Monitoring, ESP-32.
An Ensemble Approach to Improve Homomorphic Encrypted Data Classification
Performance
Dana Alsagheer and Hadi Mansourifar, University of Houston
ABSTRACT
Homomorphic encryption (HE) permits users to perform computations on encrypted data without
first decrypting it. HE can be used for privacy-preserving outsourced computation and analysis,
allowing data to be encrypted and outsourced to commercial cloud environments for processing
while encrypted or sensitive data. HE enables new services by removing privacy barriers
inhibiting data sharing or increasing the security of existing services. A convolution neuralnetwork (CNN) can be homomorphically evaluated using addition and multiplication byreplacing the activation function, such as Rectified Linear Units (ReLU), with a low polynomial
degree. To achieve the same performance as the ReLU activation function, we study the impact
of applying the ensemble techniques to solve the accuracy problem. Our experimental results
empirically show that the ensemble approach can reduce bias, and variance, increasing accuracy
to achieve the same ReLU performance with parallel and sequential techniques. We demonstrate
the effectiveness and robustness of our method using three datasets: MNIST, FMNIST, and
CIFAR-10.
KEYWORDS
Homomorphic encryption, activation function, ensemble approach.
Segmentation of Corpus Callosum Using Magnetic Resonance Image and Deep Learning
L. E. Mendoza1, L. Jaimes2, Z. Nieto3, 1, 2Magister, Professor, Research Professor, Faculty ofEngineering and Architecture, University of Pamplona, Colombia, 3Doctora, Professor, Researchprofessor, University of Santander, Colombia
ABSTRACTThe automatic detection of specific areas in medical images using mathematical techniques has
been growing significantly, due to the applications this allows. This article presents the results inthe automatic segmentation of the cerebral corpus callosum in cerebral magnetic resonanceimaging using Deep learning. 1450 images were used for training, each image with a resolutionof 512*512. A conditioning stage was developed to modify the contrast of the image, remove
irrelevant information and perform a pattern extraction process using wavelet transformation. The
results show the segmentation of the corpus callosum and the percentage of accuracy was
99.514%. The system was validated with 415 images.

KEYWORDS
Resonance image, cerebral corpus callosum, image segmentation and Deep learning.
Improved Speech Enhancement by Using Both Clean Speech and ‘clean’ Noise
Jianqiao Cui and Stefan Bleeck, Institute of Sound and Vibration Research, University ofSouthampton, Southampton, UK
ABSTRACT
Generally, speech enhancement (SE) models based on supervised deep learning technology, use
input features from both noisy and clean speech but not from the noise itself. We suggest herethat this ‗clean‘ background noise, before mixing it with speech, can also help SE and that is to
our knowledge not described yet. In our proposed model, not only the speech, but also the noise isenhanced initially and later combined for improved intelligibility and quality. We also present a
second innovation to capture better contextual information that traditional networks are often
poor in. To leverage both speech and background noise information and long-term context
information, this paper describes a sequence-to-sequence (S2S) mapping structure using a novel
two-path speech enhancement system, consisting of two parallel paths: a Noise Enhancement
Path (NEP) and a Speech Enhancement Path (SEP). In the NEP, the encoder-decoder structure isused for enhancing only the ‘clean‘ noise, while the SEP is used to suppress the background noisein the clean speech. In the SEP, a Hierarchical Attention (HA) mechanism is adopted to leverage
long-range sequence capture. In the NEP, we us traditional gated controlled mechanism from
ConvTasnet [2] but improve it by adding dilated convolution to increase receptive fields.
Experiments are conducted on the Librispeech dataset and results show that the proposed modelobtains better performance than recent models in terms of various measures, including ESTOI
and PESQ scores. We conclude that the simple speech plus noise paradigm that is often adopted
for training such models is not optimal.
KEYWORDS
Supervise speech enhancement, separate paths, hierarchical attention mechanism, gated control,
magnitude.
Gpt-4: a Review on Advancements and Opportunities in Natural Language Processing
Jawid Ahmad Baktash, Mursal Dawodi, and Chat GPT
ABSTRACT
Generative Pre-trained Transformer 4 (GPT-4) is the fourth-generation language model in the
GPT series, developed by OpenAI, which promises significant advancements in the field of
natural language processing (NLP). In this research article, we have discussed the features of
GPT-4, its potential applications, and the challenges that it might face. We have also comparedGPT-4 with its predecessor, GPT-3. GPT-4 has a larger model size (more than one trillion), better
multilingual capabilities, improved contextual understanding, and reasoning capabilities than
GPT-3. Some of the potential applications of GPT-4 include chatbots, personal assistants,
language translation, text summarization, and question-answering. However, GPT-4 poses several

challenges and limitations such as computational requirements, data requirements, and ethicalconcerns.
KEYWORDS
Large language models, Unsupervised learning, GPT-4, GPT -3 .
Applying Chatgtp to Tackle the Side Effects of Personal Learning Environments in Higher
Education: a Teacher and Teaching Perspective
Xiaoshu Xu1, Xibing Wang2, Yunfeng Zhang3, Xinyu Xu4, 1,4School of Foreign Studies,
Wenzhou University, China, 2Stamford International University, Thailand, 3Centre for Portuguese
Studies, Macao Polytechnique University, Macao
ABSTRACTThis paper explores the potential of using ChatGTP, a large language model, to address the side
effects of Personal Learning Environments (PLEs) in higher education from the perspective ofteachers and teaching. The study employed an interview method with six professors and two ICT
experts in higher education to gather data on the challenges faced by learners in PLEs and thepotential of ChatGPT to tackle these challenges. Thematic analysis was used to analyze the data,
and the results revealed that teachers face several challenges in PLEs, including educational
philosophy (e.g., pedagogy) and skills (e.g., assessment and evaluation, pedagogical design,learner engagement, and digital literacy). The lack of clear evaluation methods and the difficultyin assessing student learning due to the personalized nature of PLEs pose significant challenges.
Additionally, designing effective PLEs requires scaffolding and alignment with learning
outcomes. Digital literacy is also a critical factor in the adoption of PLEs, as teachers need todevelop the necessary skills to keep up with the rapid pace of technological change. The paperargues that ChatGTP can assist teachers in tackling these challenges. The paper is of value toeducators, researchers, and policymakers and the field of education technology by addressing thechallenges and opportunities of PLEs in higher education.
KEYWORDS
Personal Learning Environment, ChatGPT, higher education, teacher and teaching, side effects.
Research and Practice of a Blended Teaching Mode Based on Small Private Online Courses
Under an Informatization Background
Yan Li, Zhuoqun Lu and Heyun Liu, School of Energy and Mechanical Engineering, Hunan
University of Humanities, Science and Technology, Loudi 417000, China
ABSTRACTWith the continuous development of information technologies, the pace of education
informatization is accelerating increasingly. The traditional classroom-teaching mode cannot fully
meet students‘ learning demands. Due to the emergence of new teaching forms in the postpandemic era, rapid development of IT applications, national education-informatization policies
and deployment, and the plight of the traditional teaching mode, there is a need to explore newideas and patterns of integrating information technologies and teaching approaches. With thecourse of Heat Transfer as an example, this study expounds a blended teaching mode based on
small private online courses (SPOC) on course aims, teaching contents, teaching methods, andevaluation approaches under the background of informatization. The results show that thisteaching model can enhance students' learning effect and comprehensive ability effectively. The
rules of blended teaching were explored to guide teaching improvement.
KEYWORDS
SPOC, Blended Teaching, Informatization.
Significance of Special Education to the Educational Growth of a Nation
Gabriel Solomon, Pastor New Heritage Baptist Church, Nigeria.
ABSTRACTThis paper examined ―fundamental tips for understanding special education‖ an education that is
structured to meet the needs of children living with disability. The paper employed an interview
technique to gather information on the issues in special education and relevance of special
education from ten (10) teachers in special schools. Content analysis was used to report thefindings of this paper, and the findings revealed that issues in education include disability
classification, classroom environment and fund issues. In addition, the paper revealed that thesignificance of special education include it helps teachers to understand individual differences,improves motor skills, the child‘s self-esteem and help children living with disability to maintaina healthy and balanced lifestyle. This paper is of significance to educators, researchers, andcurriculum developers and educational sectors as it addresses the significance of special
education on the educational growth of a nation.
KEYWORDS
Significance, Special education, Educational growth.
Subtypes of Developmental Dyslexia
Julia Koifman, Beit Ekstein Rupin high school, Emek Hefer, Israel
ABSTRACT
In light of teaching students with dyslexia and other learning difficulties (LD), neuroscientists
claim that such deficiencies happen due to a neural base, depending on biological andenvironmental factors, and experience developing properties and improving reading skills. The
research claims two types of dyslexia: developmental (or innate) and deep (or acquired due tobrain traumas or diseases). This article researches developmental dyslexia (DD), which may be
primary and secondary. DD is divided into two main subtypes: surface and phonological While
reading; our brains must "rewire" neural circuits initially used for other tasks, such as visual andspeech processing and attention and cognition. Psycholinguistics investigates the cognitive
process of perception, production, and general use of language. This article revises teaching

English in light of neuroscience, psycholinguistics, and appropriate methods to train working
memory and other ways to overcome DD and its subtypes.
KEYWORDS
developmental dyslexia, neurodiversity, special education, working memory, neuroscience.
Breaking Barriers: Fostering Teacher's Empathy and Attitude Towards Inclusion inIndonesian Kindergartens
Khofidotur Rofiah1, 2 and Joanna Kossewska1, 1Pedagogical
Poland, 2Universitas Negeri Surabaya, Indonesia

Universityof

Cracow,

ABSTRACTIn early childhood education settings in Indonesia, there is a lack of research on teachers' attitudes
toward inclusion and the relationship between that attitude and their empathy in the context ofincluding children who have emotional and behavioral disabilities in their classrooms. Using theMultidimensional Attitudes toward inclusive educational scale (MATIES), which has three subdimensions: cognitive, affective, and behavior, and Empathy Quotient (EQ) to measure theempathy level. The purpose of this paper was to identify the connection between empathy andattitude among teachers of childhood education. In addition, this study also identified somespecific variables, namely level of education, teachers' training in inclusion, and teaching period
in relation to their attitude toward the inclusion of children with disabilities in regular classes. A
survey was given to 161 Indonesian teachers, and five participants were also asked to take part ina semi-structured interview. The findings indicate that there was a significant correlation between
the level of empathy and the three dimensions of teacher attitude towards inclusive education
including.
KEYWORDS
teachers' attitudes, empathy, Indonesian inclusive education.
Social Media Implementation as a Pedagogical Tool
Ajla Aljović, International Burch University, MA student of English Language and Literature,
Sarajevo, Bosnia and Herzegovina
ABSTRACTTechnological innovations have impacted how we teach, learn, and communicate in the
educational setting. Educational institutions must integrate various technologies, including
images, music, video, and an infinite number of online platforms, to continuously adapt to newtechnologies. Early childhood programs, which have been offered at primary education
institutions and which are being taught at universities, are specifically urged to use digital media
as a way to clearly and effectively convey a range of subject matter (Cardinal, 2017; Casey et al.,2017; Tiernan, 2015). The study argues for the educational value of social media while also
cautioning readers about the risks associated with unsupervised and unguided use by students ofsocial networking sites. Social media cannot be disregarded because it is a part of young students'

daily lives in over 90% of cases. In addition to having a large capacity for data uploading andsharing, these websites also offer some distinctive qualities including being speedy, affordable,
secure, creative, pleasant, and multimedia. No teacher can afford to ignore the influence; it would
be wiser to take it into account while planning lessons. The author cites numerous sources toshow how some SNSs, like Facebook, Twitter, LinkedIn, YouTube, etc., can be integrated. The
author does, however, offer some warnings regarding issues like privacy, time loss, distractions,and the mechanical nature of these SNSs. In the concluding lines, the author discusses various
SNS-related consequences for teachers and students and education in general.
KEYWORDS
Social networking sites, pedagogical tool, educational value, social media, teaching.
Women and Rape Culture in India: a Re-viewing of the Multifaceted ‘aahhh’ Voice andBlood-cases!
Suparna Roy, Assistant Professor, Global Institute of Management and Technology, West
Bengal, India
ABSTRACT
Rape and Sex are terms highly ambiguous and complexly ‗republicized‘ within its domain of purecultural representation. Focusing on the concept of Women as the rape victims here, it is crucial
to comprehend what we even understand by the definition of women. Is it what Women identify
and relate with their experience or are trying to uplift and mold themselves with certain featured
definitions that are patriarchally encoded to fit themselves into the definition of woman as an
identity? Remembering the definition put forward by Judith Butler in Gender Trouble regarding
the concept and definition of Women, where she said- ―Women are the sex which is not ―one‖.
Within…a phallogocentric language, women constitute the unrepresentable…women represent
the sex that cannot be thought, a linguistic absence and opacity‖. Following the queer-poststructuralist-feminist theory, this essay would re-read the cultural-politics around the discourse ofrape on women by focusing on few Rape reports, under an empirical and observational
methodology followed by an intersectional perspective.
KEYWORDS
Rape, Women, India, Culture, Society.
A Profound Look Into Teachers’ Reflective Spiral Leading to Professional Learning
Nevine El Souefi, CEO Edupedia, Egypt
ABSTRACTThis study digs deeper into the reflective process trying to understand what happens through it,
and how teachers learn from considering their own experiences. Seven teachers participated in the
study going through reflective tasks, then data was collected through a focus group discussion
with all participants, and three in-depth interviews. The study resulted in identifying the facetsthat the reflective spiral goes through. By introducing reflective tasks, reflective thinking on-

action is promoted where teachers reflect on the practice, getting the unconscious to conscious, toexpression, to put in focus. When analysing the experience, teachers go into critical reflection
resulting in awareness of the teacher as what needs to change and why. This is followed byreflective action; taking the decision to take an action, and the actual change of practice. Throughteachers‘ action in the class another type of reflection appears; reflective thinking-in-action,
considering their actions while they are teaching based on students‘ reactions, starting anothercycle of reflective thinking-on-action, or reflective thinking-in-action, and so on.
KEYWORDSThe Reflective Spiral, Professional Learning, Reflective Thinking in-action, Reflective Thinking
on-action, Critical Reflection, Reflective Action.
The Analysis of Sampling Techniques and Related Approaches - A Review
Princy Yadav, Department of Mathematics, Chandigarh University, Mohali, Punjab
ABSTRACT
Various research fields require different sampling techniques for conducting the researchefficiently. It is very essential to choose the adequate technique of sampling. This paper gives anidea on different sampling techniques and their importance in different fields. In this paper, we
discuss sampling and various types of sampling techniques. We go through two types of samplingtechniques i.e., probability and non- probability sampling techniques. We study theirsubcategories. Further, we discuss the pros and cons of these techniques. Discussing different
sampling techniques and their pros and cons will give the reader better understanding of thesampling techniques. It will help the reader to choose the right sampling technique for particularresearch. Choosing the correct sampling technique is very important for research. If a researcher
knows well about different sampling techniques, he can choose adequate sampling technique forhis research work. The aim of the study is fulfilled when a researcher understands whichsampling technique is good for his research.
KEYWORDS
Population, Sampling, Sampling Techniques, Probability Sampling, Non-Probability Sampling.
A Possible Resolution to Hilbert’s First Problem
Rajah Iyer,Microsoft, Redmund, Seattle, USA, R&D
ABSTRACT
We present herein a new approach to the Continuum hypothesis CH. We will establish atechnique for forming a subset K of R, further to this, we will extend the logical premise of
Cantor‘s Diagonal Argument to devise a means by which the cardinality of K is establishedbetween (N,R) respectively.

KEYWORDS
Diagonal Argument, Continuum Hypothesis CH, Resolution to CH
Optimizing Similarity Threshold for Abstract Similarity Metric in Speech Diarization
Systems: A Mathematical Formulation
Jagat Chaitanya Prabhala, Dr. Venkatnareshbabu K, Dr. Ragoju Ravi, Department of Applied
Sciences, National Institute of Technology, Goa, India
ABSTRACTIn this research, we propose a novel approach for speaker diarization, which is the process ofdetermining who spoke when in an audio or video recording that contains unknown amount ofspeech from unknown speakers and unknown number of speakers. Speaker diarization has several
applications in the field of speech processing and is often used as a pre-processing step. However,traditional supervised and unsupervised algorithms for speaker diarization have limitations, suchas the high cost of providing exhaustive labeling for training datasets in the case of supervised
learning and compromised accuracy when using unsupervised approaches.
To address these limitations, we propose a method that utilizes x-vector embedding, abstract
similarity metrics, and a combination of graph theory, matrix algebra, and genetic algorithm. We
also introduce the concept of loosely labeled data and demonstrate how our approach effectively
clusters temporal segments into unique user segments for speaker diarization.
We evaluate the performance of our proposed algorithm on audio recordings in English, Spanish,
and Chinese and compare it with well-known similarity metrics. Our results demonstrate that ourapproach effectively optimizes the speaker diarization process and outperforms traditional
methods. This research has significant implications for various applications in speech processing
and has the potential to improve the performance of other related tasks.
KEYWORDS
signal processing, speaker diarization, discrete optimization, neural networks
Hybrid System Approach to Math and Science
Bradford Hansen-Smith, USA
ABSTRACT
To introduce folding circles at the same time we are drawing pictures and making symbols ofthem is one thing we can do to enlarge our approach to math and science. It brings 2-D and 3-D
together through the movement of folding the circle that is not predictable by either one of them.
If it were so, we would already be doing it.
KEYWORDS
Geometry, folding circles, symmetry, unity

M.E.M.S. Which Allow the Extraction of Vacuum Energy Conform to Emmy Noether
Theorem
Dr SANGOUARD Patrick, France
ABSTRACTThis theoretical work corresponds to the hope of extracting, without contradicting EMMYNOETHER's theorem, an energy present throughout the universe: that of the spatial quantum
vacuum! This article shows that it should be theoretically possible to maintain a continuous
periodic vibration of a piezoelectric structure, which generates current peaks during a fraction of
the vibration period. Electronics without any power supply, then transform these alternating
current signals into a usable direct voltage. To manufacture these different structures, we alsopresent an original microtechnology to realize elec-tronics, and for controlling the very weakinterfaces between the Casimir electrodes and of the return electrodes! These vibrations are
obtained by controlling automatically and at appropriate instants the action of the attractive
Casimir force by a repulsive Coulomb force applied to return electrodes. The Casimir force
deforms a piezoelectric bridge, his internal field attracts opposing moving charges used togenerate an opposing Coulomb force.
KEYWORDS
Casimir, Coulomb, Vacuum Quantum Energy Extraction, Piezoelectric, MEMS
Moving Target Detection Using Ca, So and Go-cfar Detectors in Nonhomogeneous
Environment
Abdel Hamid Mbouombouo Mboungam1, Zhi Yongfeng2, Wilfried Andre Tiako
Youani3, 1Doctorate Student, School of Automation, Northwestern Polytechnical University,
Xi‘an, Shaanxi, 710072, China, 2Professor, School of Automation, Northwestern Polytechnical
University, Xi‘an, Shaanxi, 710072, China, 3Doctorate applicant, Mechanical Engineering,Northwestern Polytechnical University, Xi‘an, Shaanxi, 710072, China
ABSTRACT
Modernization of radar technology and improved signal processing techniques are necessary to
improve detection systems in complex situations. A fundamental problem in radar systems is toautomatically detect targets while maintaining a desired constant false alarm probability. This
work studies two detection approaches, the first with a fixed threshold and the other with anadaptive one. In the latter, we have learned the three types of detectors CA, SO, and GO-CFAR.
This research aims to apply intelligent techniques to improve detection performance in anonhomogeneous environment using standard CFAR detectors. The objective is to maintain thefalse alarm probability and enhance target detection by combining intelligent techniques. With
these objectives in mind, implementing standard CFAR detectors is applied to nonhomogeneousenvironment data. The primary focus is understanding the reason for the false detection when
applying standard CFAR detectors in a nonhomogeneous environment and how to avoid it using
intelligent approaches.

KEYWORDSCFAR detector, detection, adaptive threshold, non-homogeneous, false alarm probability.
Venus Electric: Phenomenology of the Venus Cycle as Evidence of Emf Ontology
L.P. Streitfeld, Independent Scholar
ABSTRACTThis paper presents an ontology of the synodic Venus cycle in the context of a third theory ofphysics (IJRAP 11). With the purpose of grounding Pauli‘s prophecy of the Aquarian icon arisingunder the collapsed quantum wave (IJRAP 10), a phenomenological experiment changed thequality of the field to facilitate manifestation. The Hieros Gamos Project released quanta in theform of alchemical art stored for Pauli‘s timing mechanism. Triggering the EMF in the humanbody via live interactive performance, the quanta/qualia marriage of pioneering an invented ―cocreation with intention‖ art/physics techne produced iconography synchronized with a visible
EMF trajectory of inner/outer embodiment. This ontological leap ―beyond Uncertainty‖ utilizes
the holistic brain to prove ―Electric Venus‖ accessed by inventors was that of ancient Sumerian
mythology. The result is an evolutionary template for restoring the holistic face of the bipolar
feminine in science — along with the Pauli origin of her magnetic attraction.
KEYWORDS
electromagnetics, quantum physics, phenomenology, ontology, hierosgamos.
Some Theoretical Aspects of Hydrogen Diffusion in Bcc Metals at Low Temperatures
Serhii Bobyr and Joakim Odqvist, KTH Royal Institute of Technology, Department of Materials
Science and Engineering, Brinellvägen 23, SE-100 44, Stockholm, Sweden.
ABSTRACT
Diffusion of H in Fe and other metals is very important as it leads to engineering problems
associated with hydrogen. The modern ab initio modeling will provide a good description of thegeometry, energy, and potential energy surface in Me-H systems. However, there is no systematic
derivation of the diffusion coefficients in which quantum-statistical effects are considered in awide temperature range.
KEYWORDS
hydrogen diffusion; bcc metals; migration of atoms; statistical model; pre-exponential factor; lowtemperature; quantum-statistical effects.
On the Limits of Pendulums: an Analysis of Horizontal Deviations and Amplitudes ofPendulums in the Detection of Gravitational Waves
Adrian Richard Cruz Salazar, University of the Philippines Manila, Ermita, Manila, Philippines.

ABSTRACTIn the detection of the very first gravitational waves, certain pieces of sensitive equipment wereneeded. This was mainly because of the small effects of gravitational waves coming from distantsources. In order to accurately detect these waves, pendulums were used, and the principles
governing pendulum motions were utilized in studying the deviations in measurement caused byexternal disruptions. This study focuses on finding the relationship of these deviations to the ratioof the amplitudes of the mass of a pendulum and its pivot point or shaft. In order to accomplish
this, calculations were performed involving different cases of simple pendulum motion. The
mechanism of the pendulum is needed in order to accurately stabilize a mirror used in detecting
gravitational waves. Better detection of gravitational waves is achieved using pendulums for
detectable vibrations as these waves have minimal observable effects brought by the long
distances of their source to Earth. Horizontal deviations for the pendulum shaft and mass werededuced. Calculations reveal that the ratio of the amplitudes of the mass and shaft is within arange that depends on the horizontal deviation of the pivot.
KEYWORDS
Pendulum, Amplitude, Gravitational Waves.
Massive Photon Hypothesis Opens Doors to New Fields of Research
Henri Corniere, Canada.
ABSTRACT
Mass, an inherent property of matter, is calculated directly for the photon particle from the very
classical principles of the kinetic theory of gases. That concept of photon mass is nearly as old asphysics itself and in fact nothing prevents this approach to be carried out for a so-called quantum
particle, not even its minute size. It is not an end result with no perspective nor other outcome.
Quite the opposite, a single ponderable tiny photon frees the mind of old ways of thinking andopens up new paths to a broad field of investigation where the very large can then be describedand explained by the very small. This reality of a non-zero mass suddenly shows up in theinterpretation of many experiments which become clear and simple to comprehend. Besides, thatsame key particle has the potential to unlock and solve some long lasting major observational
issues or enigmas. All this converges upon its acknowledgement and acceptance.
KEYWORDS
photon gas, photon mass, CMB radiation, speed of light, photon drag, viscosity.
Room Service Drone Using Feature Detection
Shorup Chanda, Department of Mechanical Engineering, Bangladesh University of Engineeringand Technology, Zahir Raihan Road, Dhaka – 1000, Bangladesh

ABSTRACTIn this current world, hospitality industries are growing at a large scale for tourists. Introducing
drone services can add an extra feature of interest to the customers and these hospitality industries
can improve customer service and can open a new scope of business. For this reason, many
hospitality industries are implementing drone services for surveying their places, taking
photography and make a 3D map of area. This project deals with a room service system in aninternal environment of a building where it will deliver foods, necessary items from room toroom. In our self-assembled and manually controlled drone, real time feature detection method
using KNN method has been implemented to detect the room number during flight and deliver
the products to the customers in their rooms.
KEYWORDS
Room Service, Number Detection, Feature Detection, KNN, Pixhawk.
Chatbots using Machine Language: Mood Analyzer and a Political Commentator
Ujjwal Nayan
Amity Institute of Information Technology (AIIT), Amity University, Noida, Uttar Pradesh
ABSTRACTThe use of chatbots is rapidly increasing in various fields such as customer service, healthcare,education, and e commerce. The advancement in Natural Language Processing (NLP) andMachine Learning (ML) techniques has led to the development of more sophisticated chatbots
that can understand and respond to human language in a more effective manner. OpenAI is aworld-renowned artificial intelligence research organization dedicated to advancing thecapabilities of AI and making it more accessible toindividuals and businesses alike. One of theirlatest offerings is a powerful AI language model called GPT-3, which is used to develop a Mood
Analyzer and a Political Commentator chatbot. This research paper aims to explore the featuresand functionality of the Mood Analyzer and Political Commentator chatbot in OpenAI's GPT-3
model, and how they can be used to analyze and interpret human emotions and political
discourse. By leveraging machine learning algorithms, a comprehensive analysis of text data
could be performed, enabling users to gain insights, and understanding into the sentiment andtopics discussed in the text input.
KEYWORDS
Chatbot, Natural Language Processing, OpenAi, Mood, Bias, Analysis.