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A new Wi-Fi symbol shaped microstrip antenna for the fifth generation (5G) applications

AIP Conference Proceedings 2022年第1期2386卷

作者： Bassam R. Mohammed Doaa M. Abbas Haidar Zaeer Dhaam 1Department of Computer Techniques Engineering College of Technical Engineering University of Al-Kafeel Iraq 2Department of Laser and Electro Optics Technical Engineering Technical Engineering College\Najaf Al-Furat Al-Awsat Technical University (ATU) Iraq

This paper introduces a new design of an antenna called a WI-FI shape microstrip antenna (WI-FI SMA). The simulator CST Studio Suite 2018 is used in the design. The band frequencies achieved from results consider one requirement of the 5G applications. The WI-FI SMA antenna operating at a resonating frequency of 29.321 GHz with reflection coefficient of −29.63 dB. The value of radiation efficiency is 99%, this value is considered very high compared with other researches. High gain was obtained (5.67 dB) with −2 dB sidelobe. The port that used in WI-FI SMA is called Waveguide feedline port. The smaller antenna size, more suitable for communication equipment and broadcasting stations.

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Node MCU based DoS attack evaluation in IoT device

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AIP Conference Proceedings 2022年第1期2519卷

作者： G. Amudha P. Prem Priya V. Dinesh A. Akash 1Department of Computer Science and Engineering RMD Engineering College Kavaraipettai Tamil Nadu India 2Department of Computer Science and Engineering RMK College of Engineering and Technology Thiruvallur Tamil Nadu India 3Software Developer Virtusa Pvt. Ltd Chennai Tamil Nadu India

In the Internet of Things (IoT) projects Node MCU ESP12 controller chip is used. During the assault simulation, it is necessary to access the safety and capacity of such a simple device in developing a number of projects that address the Internet of Things to influence system security. This device can stop the various findings that indicate the sort of attacks that spread, the incapacity of withstanding these attacks, and the *** audit archive refines the appropriate threat model for the security of WSN and IoT-based correspondences. It analyses the security demands, numerous potential risks, and various scenarios in WSN-based and IoT-based communications. Different designs of correspondence conditions are viewed as development at that time, based on WSN and IoT; the present problems and advancements in WSN and IoT are analyzed. A logical structure of security and assurance may be observed in WSN and IoT to secure the show. For feasibility, a number of investigations should be followed in this post. To show the network security choices from the integrated IoT-WSN, it is tabulated from the performance data.

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A survey on solving dilemmas of adapting blockchain in different applications

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AIP Conference Proceedings 2022年第1期2460卷

作者： C. Vijayalakshmi S. Metilda Florence S. Suthir 1Department of Computer Science and Engineering SRM Institute of Technology and Science Kattankulathur Tamilnadu India 2Department of Computer Science and Engineering Panimalar Engineering College Chennai Tamilnadu India 3Department of Information Technology SRM Institute of Technology and Science Kattankulathur Tamilnadu India 4Department of Computer science and engineering VIT Bhopal University Madhya Pradesh India

This work is going to address the dilemmas and challenges that researchers face when selecting blockchain to solve a problem in a particular domain. Since blockchain is an emerging technology and it is intended to solve many security issues in various domains, People have confusion when to use blockchain and when not to use it. The aim is to investigate which are the different applications where blockchain technology can be a solution and also it aims to discuss which type of applications does not need blockchain to be incorporated. The main contribution of this paper is Survey on blockchain technology analyzing when to use blockchain technology, Survey on when need not use blockchain technology, some research problems where blockchain can be implemented and a final discussion about blockchain adaption.

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High-end image classification on the dogs vs. cats dataset using convolutional neural network

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AIP Conference Proceedings 2022年第1期2481卷

作者： P. Chutani S. Gulati N. Arora 1EEE Department Technology Education and Research Institute Kurukshetra India 2Department of Computer Science College of Engineering Roorkee India 3School of Computing University of Engineering and Technology Roorkee Uttarakhand India

The enormous benefits and applications of Image classification and recognition are umpteen. Machine learning algorithms and Deep Neural Networks are like windfall to fathom the objective proficiently in streamlined manner. The prevalent improvement in this technology is that these networks do not call for any prior blueprints in terms of algorithms as prerequisites. The presented paper is an attempt to create a Convolutional Neural Network from scratch to classify the images from the well-known dataset – Cats and Dogs into their relevant baskets. Manifold open source accessible approaches to amplify the efficiency of the network are no more onerous. Further, data augmentation technique boosts the efficiency tremendously by extending the dataset with reoriented features from the same images. To untangle the same problem, Transfer Learning is also a compelling technique in which all the layers, neurons in each layer, weights of each neuron and all other parameters are predefined and we can amend the output layer as per the classes in the respective problem statement. In the present paper, we have tried to obtain a comparable efficiency with a significant reduction in parameters.

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A design of four port CP-MIMO system based on hexagonal ring with dual band-notch characteristic

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AIP Conference Proceedings 2022年第1期2547卷

作者： Alyaa S. Abdullah Seham A. Hashem Mahmood F. Mosleh 1Computer Techniques Engineering Engineering Technical College Middle Technical University Baghdad Iraq 2Department of Technical Electronic Technical Instructors Training Institute Middle Technical University Baghdad Iraq

In this paper, a dual-band Circularly Polarized (CP) compact-sized four elements Multi-Input Multi-Output (MIMO) antenna is presented. The proposed MIMO system consists of four monopoles radiating elements with the same hexagonal shape, and each one has three hexagonal rings. The orthogonal geometry of the proposed antenna is used to provide good isolation and polarization diversity. The dual-band notches are achieved, 3.28–3.77 GHz (13.9%; fc 3.53 GHz) for the lower operating frequency band and 4.02–7.79 GHz (63.84%; fc 5.9 GHz) for a higher operating frequency range. Moreover, the evaluation of MIMO antenna performance shows good diversity performance with Envelop Correlation Coefficient (ECC) less than 0.01, and Diversity Gain (DG) nearly 9.99 dB. The proposed dual-band orthogonal port MIMO antenna is proper for Wi-MAX and WLAN wireless applications.

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Data mining technology information integration for maximum entropy classification models

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AIP Conference Proceedings 2022年第1期2519卷

作者： R. Meenakshi K. Meenakshi M. D. Ashfaqul Hasan S. Prabagar 1Department of Computer Science Engineering Chennai Institute of Technology Chennai Tamil Nadu India 2Department of Computer Science Engineering SRM Institute of Science and Technology Vadapalani Campus Chennai Tamil Nadu India 3Department of Computer Science Engineering Mallareddy Institute of Engineering and Technology Hyderabad Telangana India 4Department of Computer Science Engineering Nalla Malla Reddy Engineering College Hyderabad Telangana India

If sample data disperses information like classification rules, these regulations can need to be combined and fused. This is usually done by combining either the classification outputs, like the classification ensemble, or by incorporating the collection of classification laws by independently weighing them. In this paper, we introduce a new way of assembling classifiers with parameters of classifiers. The technique is based on the use for regression analysis distributions in normative input dimensions of generative probabilistic graders and on nonparametric wave function for continuous. We also spread over classification parameters such as Dirichlet or regular Wishart. These populations are classified as populations of high or second order. We prove that two or more classificatory can be used by multiplying the hyper distributions of variables and drawing simple formulas for the assignment. Any research reveals how this modern approach is described. The primary advantage of this fusion approach is the conservation of hyper distribution in the fusion phase. For starters, the fused components can be used in the organized training steps.

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Design implementation of smart fish pond monitoring system using IoT

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AIP Conference Proceedings 2023年第1期2523卷

作者： S. V. Tresa Sangeetha P. G. Kuppusamy V. Chandrasekaran A. Sangeerani Devi 1Department of Engineering University of Technology and Applied Science-Al Mudabah Muladdah South Batinah Sultanate of Oman. 2Department of Electronics and Communication Engineering Siddharth Institute of Engineering and Technology Puttur Andhra Pradesh India 3Department of Medical Electronics Velalar College of Engineering and Technology Thindal Tamil Nadu India 4Department of Computer Science and Engineering Sri Sairam Engineering College Chennai Tamil Nadu India

The present approach aims to provide safe and safe production of high-quality seafood by keeping regular levels of water in the fish tank by helping fish pool owners. The flow of high or low water into the fish pond solves the problem of killing fish in a fish tank for the long term. Every grade of water can impact animal health alone. The water flow in fish ponds describes how to check it every day. We need to check the parameters of the water on a regular basis. It symbolizes high water quality standards and bad water quality ponds and how they need to be improved. It is advised that the precondition for increasing output should be given priority to guarantee sustained fresh quality. Water quality parameters therefore maintain a balance; culture is the cornerstone for living creatures' health and growth. The water quality metrics should be monitored and evaluated regularly.

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Sedimentary aquifer accessing using 2-D resistivity imaging, case study: Blang Bintang, Aceh Besar

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AIP Conference Proceedings 2023年第1期2613卷

作者： Muhammad Syukri Zul Fadhli Amsir Sabrian Tri Anda Rini Safitri 1Department of Physics Faculty of Sciences Syiah Kuala University Darussalam Banda Aceh 23111 Indonesia. 2Department of Geophysics Engineering Faculty of Engineering Syiah Kuala University Darussalam Banda Aceh 23111 Indonesia. 3Faculty of Computer and Multimedia University of National Islamic Indonesia Indonesia

Water is a major issue that faced by the settlement area in most country around the world. Moreover, if the settlement is located in metropolis city. Based on those reasons, the authors triggered to conduct the study regarding the identification of potential aquifer. The study carried out in Blang Bintang (Aceh Besar) by utilized 2D resistivity method. The 2D resistivity survey lines were conducted with 5 m minimum electrode spacing using pole-dipole array, and the results validated with existing borehole record. The bore-log identified aquifer zone located between sandy clay and clay with depth of 56-67 m. The 2D resistivity results shows the aquifer layer located at depth of 55-70 m with resistivity value of 30-45 Ωm. Both data are significantly consistent. It can be concluded that the aquifer can be identify using 2D resistivity imaging using any available array, but the resistivity values vary depend on their geology setting.

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Impact of base learning dataset on transfer learning for maize disease detection

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AIP Conference Proceedings 2022年第1期2357卷

作者： Subodh Bansal Anuj Kumar 1University Institute of Engineering and Technology Panjab University Sector 25 Chandigarh India 2Department of Computer Science and Applications Panjab University Sector 14 Chandigarh India

Transfer learning is an effective technique to train a Deep Learning Model (DLM) on small datasets. The researcher implemented this technique for Maize Disease Detection and achieved a classification accuracy of 94.56%. Further, the nature of the base learning and fine-tuning datasets were compared, to analyze their impact on the DLM model. The comparison was done using four mutually exclusive scenarios: (A) No base learning, (B) Base learning on general-purpose dataset, (C) Base learning on healthy plant leaves, and (D) Base learning on a mix of healthy and diseased plant leaves, by excluding Maize images from them. The results of the experimentation conclude that the base learning dataset has a significant impact on transfer learning for Maize disease detection. Thus, the base learning dataset should be carefully selected, as unrelated datasets can deteriorate the results.

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Developing a classifier model to analyze and predict cancer mellitus

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AIP Conference Proceedings 2022年第1期2519卷

作者： K. Suresh S. V. Sugin V. Kavitha 1Center for Artificial Intelligence Chennai Institute of Technology Chennai. Tamilnadu India 2Department of Computer Science and Engineering Kings Engineering College Chennai Tamilnadu India 3Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur Chennai Tamilnadu India

The main objective of this paper is to be lowered to a minimum of delay and not to provide an early forecast of cancer of lung cancer in patients, but also and not to reduce the need for biopsy. In addition, it gives and comparisons between different algorithms for classification. Existing models use a CT scan to predict lung cancer but are also well equipped with sufficient data to predict precisely. The model was developed based on a support vector machine, which provides 92 % accuracy. Because it is required solutions, for to be increased right speed for prognosis of cancer of lung cancer. The proposed solution uses a set of data for classification and has approximately 300 observations. The model is developed for different algorithms for classification, such as arbitrary attendant’s vectors, K-nearest-neighbors, and Naive-Bayes are compared to a - great accuracy. It provides an early prognosis of cancer of lung cancer with high accuracy. Therefore, the proposed decision model based on Naïve Bayes achieved the highest degree of accuracy of 95.23%.

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