Showing papers in "International Journal of Computer Applications Technology and Research in 2023"

5G Wireless Technology- An overview of the current Trends

Abstract: 5G Wireless technology networks or 5th Generation wireless systems which is used for videos and audios communication announcement the next major time period of mobile telecommunications Criterions time the current next Generation mobile networks confederated .in this paper we are studying different Technologies in 5G The handover of 5G the Models of 5G its architecture, its different components and METIS Task Force Networks. 2-Day video recording is available. Its components access/backhaul integration, direct device-to-device communication, flexible duplex, flexible spectrum usage multiantenna transmission, ultra-lean design, user/control separation architecture of 5G is highly advanced, its network elements and various terminals are characteristically upgraded to afford a new situation. Likewise, service providers can implement the advance technology to adopt the value-added services easily.

Development of Online General Chemistry Teaching Materials Integrated with HOTS-Based Media Using the ADDIE Model

Abstract: The 21st century education system prioritizes students to have critical, creative, collaborative thinking skills and communication skills, including higher-order thinking skills. This study aims to develop online teaching materials for HOTS-based integrated General Chemistry courses using the ADDIE model to improve students' higher order thinking skills. This development research resulted in HOTS-based integrated online teaching materials that were feasible and effective in improving students' higher order thinking skills. Through the HOTS-based media integrated online teaching materials produced, students are required and trained to be able to think critically, creatively, analytically towards existing information and data and have the ability to solve problems.

Test-Case Optimization Using Genetic and Tabu Search Algorithm in Structural Testing

Abstract: Software test-case generation is the process of identifying a set of test cases. It is necessary to generate the test sequence that satisfies the testing criteria. For solving this kind of difficult problem there were a lot of research works, which have been done in the past. The length of the test sequence plays an important role in software testing. The length of test sequence decides whether the sufficient testing is carried or not. Many existing test sequence generation techniques uses genetic algorithm for test-case generation in software testing. The Genetic Algorithm (GA) is an optimization heuristic technique that is implemented through evolution and fitness function. It generates new test cases from the existing test sequence. Further to improve the existing techniques, a new technique is proposed in this paper which combines the tabu search algorithm and the genetic algorithm. The hybrid technique combines the strength of the two meta-heuristic methods and produces efficient testcase sequence.

Object Oriented Software Testability (OOST) Metrics Analysis

Abstract: One of the core quality assurance feature which combines fault prevention and fault detection, is often known as testability approach also. There are many assessment techniques and quantification method evolved for software testability prediction which actually identifies testability weakness or factors to further help reduce test effort. This paper examines all those measurement techniques that are being proposed for software testability assessment at various phases of object oriented software development life cycle. The aim is to find the best metrics suit for software quality improvisation through software testability support. The ultimate objective is to establish the ground work for finding ways reduce the testing effort by improvising software testability and its assessment using well planned guidelines for object-oriented software development with the help of suitable metrics.

Application Interactive Thematic Learning Media i-Spring to Improve Student Learning Outcomes

Abstract: The purpose of this study was to determine the level of feasibility of using interactive thematic learning media for the application of i-spring to elementary school students. Development research methods (Development & Research). Development research is a model in research that is used to produce certain products and to test the feasibility of media and the effectiveness of a product. The subjects in this study were students of class III A at Tembung 101767 Elementary School. The location of this research was carried out at elementary school IT Nurul 'Ilmi in the odd semester of the 2022/2023 academic year. This development research focused on thematic learning, namely theme 3 "Things Around Me", sub-theme 2 "Objects Being" and Learning 5 and 6 in class III elementary school. The final product will be evaluated based on the specified product quality aspects. The results of the study show that the Thematic Interactive Learning media in the thematic learning developed has been validated and meets the criteria for good and appropriate learning media to be used in thematic learning on the theme 6 sub-themes 3 in class III elementary school with an average media percentage of 88% and material of 90% with a very feasible category as a learning medium.

KVM Terminal Software Design Based on RK3399 Processor

Abstract: KVM denotes the initials of the keyboard, monitor and mouse of a computer. digital KVM systems are composed of two parts, one is the device terminal and the other is the software adapted to this device terminal. KVM systems are emerging remote centralized management technologies for multiple devices in multiple locations based on IP networks in recent years [1,2]. digital KVM systems mainly use IP networks to control remote computers to control remote computers mainly through IP networks [3]. Therefore, KVM systems are widely used in computer management and remote control of computers. In practical applications, the compression efficiency of images is relatively low and the delay of mouse movements is relatively large. To address these two shortcomings, this paper designs a software based on the RK3399 processor, which on the one hand performs fast image acquisition and high-quality encoding, and on the other hand realizes input control of the target computer through the mouse and keyboard control chip UI012.

Technological View on Smart Waste Management

Abstract: The sustainable development goal of society, need of healthy environment and due to growing population quantity of solid waste increases rapidly drives the smart waste management. Since it is unhealthy for humans who involve in manual waste management those field works need automation. The Artificial Intelligence provides the way to achieve the automation to collect and process the solid waste with the help of Internet of Things, Cloud Computing and Intelligent Transport System. We explored the technological development towards the implementation of smart waste management to support further development in this domain.

Design of High-Speed SAR ADC based on 40nm CMOS Process

Abstract: In this paper, a high-speed successive approximation analog-to-digital converter is designed based on a 40 nm CMOS process. A split-capacitor Vcm-Based switching strategy is designed, which is able to keep the output common-mode voltage constant for the DAC capacitor array without using Vcm level drive, while saving half of the capacitance compared to the conventional switching strategy and greatly reducing the area consumption. It also combines the features of binary redundancy technology and non-binary redundancy technology by splitting the highest bit capacitor to the lower bit, which enables the DAC array to generate two additional redundant bits without adding other capacitors, reducing its requirements for noise and establishment accuracy; and it adopts asynchronous timing control without external clocks, which is conducive to improving the speed of SAR ADCs and reducing the design complexity. The designed SAR ADC achieves 9.83 bit effective bits, 60.9 dB signal-to-noise distortion ratio, 77.2 dB spurious-free dynamic range, 1.68 mW overall power consumption, and 18.46 fJ/conv-step superiority at a supply voltage of 1.1 V and a sampling frequency of 100 MHz through simulation.

Digital Archiving and Preservation of Cancer Records: Case of KNH/UoN Department of Pathology

Abstract: Cancer is considered to be 3rd leading killer and 2nd among non-communicable diseases in Kenya Mutinda J. (2019). Ferlay, et al (2013) noted there are about 37,000 new cases of cancer annually and annual mortality rate of 28,000. This indicates cancer records rapidly accumulate over time and more resources are needed to collect and manage cancer-related data. KNH/UoN Department of Pathology have for a long time kept their records using a paper-based system. Objective of the study was to review current record keeping system including the process of preserving, storing and retrieving cancer records and the challenges faced, develop a model to guide the archival of locally available cancer paper-records and a web based prototype to preserve and avails this information to a wide range of stakeholders. The study used descriptive research design involving 22 participants. Random sampling technique was used to select respondents among the sampled population. The intervention prototype was developed using the RAD methodology. It was noted that cancer patient data were captured through standard forms/books (86% of the respondents) and stored in standard forms/books (71% of the respondents). 57% stated that identification of record and documenting was done based on LAB number. ICD 10 Coding system was not fully implemented as many forms had old coding format. 77% of the participants stated that the inability to track patient records with ease as a challenge and lack of technology in records management as a potential security bleach and damage of records. Findings presented a strong case for this research study where, upon prototype developed, there was concurrence among the respondents that the developed solution would be of significant to enhance cancer records management in the department and improving the healthcare service delivery process. This model can also be used to preserve other similar medical paper documents.

The Analysis of Inulin From Yam Tubers using FTIR (FOURIER TRANSFORM INFRA RED)

Abstract: Research on inulin which was isolated from yam tubers (Pachyrhizuserorus).This research is a experimental laboratory research. The Qualitative Analysis of Inulin is Reduction Sugar make a Bennedictand The Quantitative Analysis Inulin was isolated from yam tubers is characterized by using Forrier Transform Infra Red (FTIR).

An Ensemble Learning Model for Predicting Social Engineering Pharming Attacks

Abstract: Pharming attack has a broad scope as social engineers can masquerade as anyone, particularly during the COVID-19 pandemic from health authorities or even organization executives getting in touch with their personnel. The study aims to develop an ensemble model for predicting social engineering-based pharming attacks from the client-side pharming attack. The target population for the study includes 1781 URLs, which are secondary and readily available on Kaggle having been compiled by Manu Siddhartha. The study focused on identifying URLs that facilitate Pharming attacks, a cybersecurity threat. Malicious URLs miss the protocol segmentation, certificate of authorization, and bait targets into becoming victims of pharming attacks. The research instrument used for data process and building a pharming attack model was CSV and Jupyter notebook. Data was collected from secondary data sources. A model for predictive pharming attacks was built utilizing Logic regression, Random Forest, and gradient boost as the model for boosting algorithms to reduce pharming malware attacks.

Design of a 14-bit Pipelined ADC using Ring Amplifier

Abstract: With the progress of integrated circuit technology, the intrinsic gain of transistors has become increasingly low, and the power consumption and complexity of OTA operational amplifiers have become higher, increasing the overall design difficulty of pipeline ADC. In order to improve the gain of the operational amplifier, improve the overall accuracy of the ADC, and reduce circuit power consumption, a 14-bit 20MSPS analog-to-digital converter with a pipeline structure of 2.5bit-2.5bit-2.5bit-2.5bit-2.5bit-2.5bit-2.5bit-2.5bit-2bit was designed using the SMIC 40nm process and analog drive digital technology under a 1.2V power supply voltage based on a new type of ring amplifier.The simulation results show that the SNDR of the input low-frequency signal pipeline ADC is 70.47dB, the SFDR is 85.5dB, and the ENOB is 11.45bit. When inputting high-frequency signals, the SNDR of the pipeline ADC is 68.35dB, the SFDR is 81.3dB, and the ENOB is 11.07bit.

Facial Expression Recognition Based on Improved Densenet Network

Abstract: As a branch of image recognition, facial expression recognition helps to carry out medical, educational, security and other work more efficiently. This article combines deep learning knowledge and conducts research on expression recognition based on DenseNet121, a dense convolutional neural network that integrates attention mechanisms for multi-scale feature extraction. Firstly, in response to the insufficient ability of DenseNet121 to extract complex facial expression features, multi-scale feature extraction dense blocks were introduced to replace DenseBlocks used to extract features of different sizes; Secondly, using multi-scale feature extraction convolutional blocks to replace the large convolutional kernel at the head of DenseNet121 further enriches feature extraction; Finally, in order to extract more important features from the channel dimension, we consider combining ECA channel attention mechanism to help improve model performance. The experiment proves that the model proposed in this chapter has improved recognition accuracy by 2.034% and 3.031% compared to DenseNet121 on the FER2013 and CK+datasets, respectively. It also has certain advantages compared to other commonly used classification models.

A Study of Approaches and Measures aimed at Securing Biometric Fingerprint Templates in Verification and Identification Systems

Abstract: The need for fool proof authentication procedures away from traditional authentication mechanisms like passwords, security PINS has led to the advent of biometric authentication in information systems. Biometric data extracted from physiological features of a person including but not limited to fingerprints, palm prints, face or retina for purpose of verification & identification is saved as biometric templates. The inception of biometrics in access control systems has not been without its own hitches & like other systems it has its fair share of challenges. Biometric fingerprints being the most mature of all biometric spheres are the most widely adopted biometric authentication systems. Biometric systems effectiveness lies on how secure they are at preventing inadvertent disclosure of biometric templates in an information system’s archive. This however has not been the case as biometric templates have been fraudulently accessed to gain unauthorized access in identification and verification systems. In order to achieve strong and secure biometric systems, biometric systems developers need to build biometric systems that properly secure biometric templates. Several biometric template protection schemes and approaches have been proposed and used to safeguard stored biometric templates. Despite there being various biometric template protection schemes and approaches in existence, none of them has provided the most authentic, reliable, efficient and deterrent means to totally secure biometric fingerprint templates. This research sought to establish status of the current biometric template protection techniques and methods by conducting a survey and analyzing data gathered from a sample of seventy-eight (78) respondents. We will report these results and give our conclusion based on findings of the survey in this paper.

Design of a High Precision RC Oscillator

Abstract: This paper introduces a high-precision RC oscillator circuit that is less affected by temperature and supply voltage. The circuit mainly consists of a bandgap reference voltage source, a low-voltage linear regulator, a low-pass filter, and a digital trim circuit, which reduces the circuit's sensitivity to temperature variations and achieves high stability of the oscillator frequency over a wide temperature range. Because of the current digital trimming technique, the circuit's ability to cope with the effects of frequency instability caused by process deviations is further enhanced.The simulation results show that the output center frequency accuracy is maintained within ±0.5% under the supply voltage range of 2.5V~5.5V, temperature range of -40?~125?, and different process corners. The RC oscillator has a high precision output frequency and can be used as a clock signal for a number of highly integrated and high precision applications.

Development of Learning Media In The Form of Microsoft Team Applications in Digital Information and Communication System Learning

Abstract: The purpose of this study was to determine (1) the feasibility of learning media in the form of Microsoft team applications in digital information and communication systems learning in class XI students of SMK Negeri 1 Idi; and (2) to determine the effectiveness of learning media in the form of Microsoft team applications in learning information systems and Digital Communication in Class XI Students of SMK Negeri 1 Idi. This type of research uses the R & D development model. The subjects of this study consisted of one material expert, one instructional media expert, one instructional design expert, and class XI students of SMK Negeri 1 Idi. The results showed: (1) the expert test of learning materials was very good (88%); (2) the expert test of learning media is very good (92.94%); (3) the expert test of very good learning design (97.35%); (4) E-Module Basic Learning Sewing Technology Based on Discovery Learning Learning Media in the form of Microsoft Team Applications in Digital Information and Communication Systems Learning is feasible to use; (4) there is a significant difference between the learning outcomes of students who use media and textbooks. This is indicated by the results of processing the data on the posttest results obtained by the price of t count = 10.691, At a significant level (? = 0.05) with dk 58 obtained ttable = 1.167 so that tcount > ttable for practical results obtained price of t count = 11.023, At significant level (? = 0.05) with dk 58 obtained ttable = 1.167 so that tcount > ttable. The average effectiveness of learning outcomes in the use of Learning Media in the form of Microsoft Team Applications is 85%, while groups of students using textbooks are 68%. This data proves that the use of Learning Media in the form of Microsoft Team Applications is more effective than without using media.

The Effect of the Learn to Sing Learning Model and Creativity on Student Arts and Culture Learning Outcomes

Abstract: The aims of this study were: (1) to determine the influence of Learn to Sing media and creativity on student learning outcomes in arts and culture subjects; (2) to know the influence of student creativity with Learn to Sing media and creativity on student learning outcomes in arts and culture subjects; and (3) knowing the interaction of Learn to Sing media and creativity on student learning outcomes in arts and culture subjects. The research method used was experimental research in the first experimental group learning with Learn to Sing using an Android smartphone and the second experimental group learning directly. Creativity is divided into high and low creativity. The research was conducted at SMP Negeri 30 Medan. The population of this study was all students of classes VIII-1, and VIII-2. The research design is presented in a 2 x 2 factorial design with the analysis of variance technique (ANOVA). The results showed that: (1) there were differences in the learning outcomes of doing Learn to Sing between groups of students who were taught by the Learn to Sing learning model and students who were taught by the direct learning model, the results of doing Learn to Sing were higher than the group of students who were taught by the learning model. direct learning where (f count = 3.38 > F table = 3.26). (2) there are differences in learning outcomes that have high creativity with groups of students who have low creativity. Students who have high creativity get high learning outcomes than the group of students who have low creativity where (F count = 11.39 > F table = 3.26). There is no interaction between the application of learning with the learning model with the Learn to Sing learning model and the direct learning model with high and low levels of creativity towards learning arts and culture outcomes by doing Learn to Sing students where (F count = 0.45 < F table = 3.26).

UVA Image Registration Model Based on VGG and Multi-Branch Attention

Abstract: For UVA images with different resolutions and large areas of weak texture, image feature extraction is insufficient and mis-matching is increased during image registration. To solve these problems, an unsupervised registration model based on VGG feature extraction and multi-branch attention is proposed. First of all, two feature extraction networks with shared weight parameters are used to extract the low and high level fusion features of the moving image and the reference image. The convolution neural network is used to extract the high-dimensional feature map of the image, and the key points are selected according to the conditions that meet both the channel maximum and the local maximum, and the corresponding 512-dimensional descriptor is extracted on the feature map, In the matching stage, add multi-branch attention based on residual block to filter out the wrong features. The algorithm is tested with multiple groups of images and compared with several image matching algorithms. The results show that the algorithm can extract the scale-invariant similar features of images, and has strong adaptability and robustness.

Huffman Algorithm Valuation Using Residue Number System

Abstract: The Huffman algorithm is a widely used method for lossless data compression, which assigns variable-length codes to characters based on their frequency of occurrence in the input data. However, the traditional implementation of Huffman coding using binary arithmetic can be computationally intensive, particularly for large data sets. In recent years, the Residue Number System (RNS) has emerged as a promising alternative to binary arithmetic for certain types of computations, due to its potential for parallel processing and reduced hardware complexity. This paper evaluates the use of RNS as a basis for implementing the Huffman algorithm, comparing its performance with the traditional binary approach. The results demonstrate that RNS-based Huffman coding can achieve comparable or superior compression ratios, while reducing the computational requirements and potentially enabling faster compression and decompression. The study also highlights the importance of choosing appropriate RNS moduli and operands to optimize performance. Overall, the evaluation suggests that RNS can be a viable and efficient alternative to binary arithmetic for implementing the Huffman algorithm, particularly in applications with high computational demands or limited hardware resources. However, further research is needed to explore the potential benefits and limitations of RNS in other areas of data compression and signal processing.