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Keyword: POSAn Advanced Algorithm Combining SVM and ANN Classifiers to Categorize Tumor with Position from Brain MRI Images
Brain tumor is such an abnormality of brain tissue that causes brain hemorrhage. Therefore, apposite detections of brain tumor, its size, and position are the foremost condition for the remedy. To obtain better performance in brain tumor and its stages detection as well as its position in MRI images, this research work proposes an advanced…
Read MoreNumerical evaluation of ABS parts fabricated by fused deposition modeling and vapor smoothing
The automotive industry has focused to use polymer materials in order to increase energy efficiency. So, the industry pays attention to use 3D printing technologies using several polymers. Among several 3D printer technologies, fused deposition modeling (FDM) is one of the popular 3D printing technologies due to an inexpensive extrusion machine and multi-material printing. FDM…
Read MoreProposal of an Embedded Methodology that uses Organizational Diagnosis and Reengineering: Case of bamboo panel company
This work is an extension of the Proceedings of the International Conference on Industrial Engineering, Management Science and Applications, which presented some of the phases of Reengineering applied to Bamboo Panel Company; the results were Strategic planning, Systemic Diagnosis and Performance Indicators through the Balanced Scorecard. Now, the main purpose of this article is to…
Read MoreProposal for a Visualization System of Purchase Relationship Using ID-POS Data
In recent years, big data analysis is gaining immense credence in the fields of academics and business. Businesses such as management and marketing have demonstrated a strong inclination and interest in data analytics. However, many businesses are unable to utilize data even if they have access to it. The main reason for that is the…
Read MoreRecognition and Position Estimation for Multiple Labware Transportation Using Kinect V2 and Mobile Robots
Mobile robots can be used to perform transportation tasks for different objects. These tasks have to be implemented carefully. Therefore, an accurate approach for object recognition and position estimation is required. This work presents a concept for identification and position estimation of multiple labware. These labware, which contain chemical and biological components, have to be…
Read MoreIoT: Their Conveniences, Security Challenges and Possible Solutions
The build-in internet-controlled functions of smart devices such as smart phone, smart television, home healthcare gadget, etc., have made them quite attractive to many segments of consumers. In recent years mankind has witnessed an upsurge usage of such devices for numerous purposes. In this paper, the author is going to show how previously forecasted security…
Read MoreHuman Sit Down Position Detection Using Data Classification and Dimensionality Reduction
The analysis of human sit down position is a research area allows for preventing health physical problems in the back. Many works have proposed systems that detect the sitting position, some open issues are still to be dealt with, such as: Cost, computational load, accuracy, portability, and among others. In this work, we present an…
Read MoreGNSS Positioning in Non-line-of-Sight Context—a Survey for Technological Innovation
Reliable, available and accurate localization of people and vehicles is one crucial requirement for intelligent transportation systems (ITSs). This has led to a variety of technical approaches in recent years. Towards an exact positioning via Global Navigation Satellite Systems (GNSSs) the visibility of satellites is an important factor. In this paper, we review the literature…
Read MoreA Theoretical and Experimental Comparison of One Time Pad Cryptography using Key and Plaintext Insertion and Transposition (KPIT) and Key Coloumnar Transposition (KCT) Method
One Time Pad (OTP) is a cryptographic algorithm that is quite easy to be implemented. This algorithm works by converting plaintext and key into decimal then converting into binary number and calculating Exclusive-OR logic. In this paper, the authors try to make the comparison of OTP cryptography using KPI and KCT so that the ciphertext…
Read MoreCombination of Caesar Cipher Modification with Transposition Cipher
The caesar cipher modification will be combine with the transposition cipher, it would be three times encryption on this experiment that is caesar modification at first then the generated ciphertext will be encrypted with transposition, and last, the result from transposition will be encrypted again with the second caesar modification, similarly at the decryption but…
Read MoreModification of Symmetric Cryptography with Combining Affine Chiper and Caesar Chiper which Dynamic Nature in Matrix of Chiper Transposition by Applying Flow Pattern in the Planting Rice
Classical cryptography is a way of disguising the news done by the people when there was no computer. The goal is to protect information by way of encoding. This paper describes a modification of classical algorithms to make cryptanalis difficult to steal undisclosed messages. There are three types of classical algorithms that are combined affine…
Read MorePreparation of Ni-C Ultrafine Composite from Waste Material
This work depicts the preparation of Ni-C ultrafine composite from used engine oil. The used oil was emulsified with detergent loaded with Ni (OH)2. The loaded emulsion was sprayed on electric plasma generated between two C electrodes to a DC main 28 V and 70-80 A. The purged Ni-doped carbon fume was trapped on a…
Read MoreA comparative between CRISP-DM and SEMMA through the construction of a MODIS repository for studies of land use and cover change
Among the most popular methodologies for development of data mining projects are CRISP-DM and SEMMA, This research paper explains the reason why it was decided to compare them from a specific case study. Therefore, this document describes in detail each phase, task and activity proposed by each methodology, applying it in the construction of a…
Read MoreA delay-dependent distributed SMC for stabilization of a networked robotic system exposed to external disturbances
In this paper, a delay-dependent controller based on the sliding mode concept is proposed to stabilize a networked robotic system in a decentralized synchronization scheme. In addition to being affected by communication time-delays between agents, and seen that external disturbances obviously affect any physical and dynamic system, an unsettling action resulting from measurement errors affects…
Read MoreL-Band SiGe HBT Active Differential Equalizers with Variable, Positive or Negative Gain Slopes Using Dual-Resonant RLC Circuits
L-band SiGe HBT active differential equalizers with variable, positive or negative gain slopes have been designed and fabricated for frequency and temperature compensation of microwave and optical systems. The active equalizer employs dual-resonant RLC circuits in the series feedback path of the differential amplifier for positive gain slopes or in the load for negative gain…
Read MoreProposal of a congestion control technique in LAN networks using an econometric model ARIMA
Hasty software development can produce immediate implementations with source code unnecessarily complex and hardly readable. These small kinds of software decay generate a technical debt that could be big enough to seriously affect future maintenance activities. This work presents an analysis technique for identifying architectural technical debt related to non-uniformity of naming patterns; the technique…
Read MoreExpression of balance function during exposure to stereoscopic video clips
Recently, with the rapid progress in image processing and three-dimensional (3D) technologies, stereoscopic images are available not only on television but also in theaters and gaming consoles. Asthenopia and visually induced motion sickness (VIMS) are well-known phenomena experienced by users while viewing video clips, playing immersive video games, and other such activities. In previous studies,…
Read MoreTL-SOC: A Hybrid Decision-Centric Intrusion Detection Framework for Security Operations Centers
Security Operations Centers (SOCs) require intrusion detection systems that achieve high detection accuracy while maintaining a low false-positive rate and robustness to evolving attack patterns. However, most existing machine learning-based approaches primarily focus on detecting known threats and often overlook distribution shifts and the reliability of generated alerts. In this paper, we propose TL-SOC, a…
Read MoreAn Ensemble Learning Approach for Student Performance Analysis of a Higher Educational Institute using a SHAP-Based Feature Selection and Optuna Optimization
Forecasting and assessing student performance are crucial for allowing educators to pinpoint deficiencies and promote grade improvement. A thorough comprehension of feature contributions is crucial for improving model interpretability and facilitating informed decision-making in academic institutions. Explainable artificial intelligence encompasses methodologies and strategies designed to deliver transparent and accessible rationales for the decisions rendered by…
Read MoreInvestigating the Influence Biomass Additive on the Thermal Performance of a Fired-Clay for Producing the Inner Liner of a Biomass Cook-Stove
This study investigated the influence of a biomass additive on the thermal performance of the inner liner of fired-clay cook-stoves. Fired-clay cook-stoves are essential cooking devices, particularly in areas with limited access to modern energy resources. The study aimed to enhance the thermal efficiency of the cook-stoves by incorporating rice husk into the inner liner…
Read MoreMulti Attribute Stratified Sampling: An Automated Framework for Privacy-Preserving Healthcare Data Publishing with Multiple Sensitive Attributes
The accumulation and analysis of large-scale patient data have led to breakthrough discoveries in potential flags for diseases based on pattern recognition, highlight medication efficacy, and local population health trends that would be impossible with traditional paper-based records. However, these benefits come with unique challenges posed by the application of data sharing for research and…
Read MoreEfficient Pattern Recognition Resource Utilization Neural Network
Neural Networks derives intelligent systems and modern autonomous applications. With the complexity introduced in today’s systems, designing architectures remains open research problem in all fields. Despite many efforts to generalize, the resources required by neural architectures remain challenge. Robots design, Smart cities, IoTs …etc. become the leading industry and driving the fourth industrial revolutions. All…
Read MoreDetection Method and Mitigation of Server-Spoofing Attacks on SOME/IP at the Service Discovery Phase
Service-oriented architecture has attracted attention in automotive development. The Automotive Open System Architecture (AUTOSAR) specifies Scalable Service-Oriented Middleware over IP (SOME/IP) as a key middleware for service-oriented communication in-vehicles. However, SOME/IP-based networks are vulnerable to server spoofing during the service discovery phase, enabling attackers to cause man-in-the-middle attacks by impersonating legitimate services. This paper proposes…
Read MoreDesign and Electronic Interfacing of FR4 and Polyimide PCB-based Electromagnetic Resonating Micro-mirrors
This paper presents the design and fabrication of an electromagnetically actuated PCB-based resonating scanning micro-mirror for LiDAR applications, with optimization targeted towards low-cost fabrication and a high scanning angle. Traditional silicon MEMS-based micro-mirrors, while offering high precision and compatibility with CMOS processing, are limited by fragility at low scanning frequencies and costly fabrication processes. To…
Read MoreFederated Learning with Differential Privacy and Blockchain for Security and Privacy in IoMT A Theoretical Comparison and Review
The growing integration of the Internet of Medical Things (IoMT) into healthcare has amplified the need for secure and privacy-preserving artificial intelligence. Federated Learning (FL) has emerged as a pivotal paradigm for decentralized medical data processing; however, it still faces challenges concerning data confidentiality, trust management, and scalability. This review presents an extended theoretical comparison…
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