bluuebunny/crossref_metadata_2025 huggingface dataset:
Network security and computer program
Authors: Qian Xinyang
Published: July 2023

In this era of rapid development of network and computer technology, the potential dangers become more and more numerous. There are many security issues that are hidden and unobtrusive. Creating a computer firewall to defend against network security leaks is a necessity. Firewalls can be personal and make a match that is more in line with what is in mind. Firewalls must allow any necessary connections from application business and technical expertise through the firewall to ensure the integrity of the data network. For firewall pairings, Border network, Perimeter Network, and Internal Network are also necessary for impact. The firewall construction can also be made more secure by implementing it through WIFI IP address. Dynamic NAT, Static NAT and PAT are essential in firewall building, and they all aim at network address translation. When building a firewall, changing a specific IP address can monitor the own network and control the message delivery in terms of security.
Comparison of processing results of median filter and mean filter on Gaussian noise
Authors: Sun Manman
Published: July 2023

In people's daily lives, if the image is polluted with noise, it will become very blurred, so it is pretty necessary to use filtering to denoise the image and get a clearer image to assist people in work and study. The purpose of this article is by comparing the denoising result of the Median filter and Mean filter on Gaussian noise, and the filtering method which is more suitable for reducing Gaussian noise is found. Matlab is a very accurate and reliable scientific calculation standard software tool, which is very common in people's lives. The Median filter is a kind of nonlinear filter. It is so virtual at decreasing impulse noise. The common basic theory of the Median filter is to supersede the gray value of pixels with the median of the gray value in a neighborhood of the pixels, and not use the average proportion. The Mean filter is a sort of plain sliding-window space filter that takes the place of the central value with the mean of all the pixel values in the plain window. This essay takes advantage of Matlab to complete the process of adding Gaussian noise in photos, reducing Gaussian noise, and calculating the PSNR. The processing result of two types of noise reducers on Gaussian noise is compared. And by observing the image clarity, PSNR and MSE evaluation techniques to find which is a better filter to decrease Gaussian noise.
Comparison among baseband codes based on MATLAB
Authors: Xiao Peian
Published: July 2023

The thesis is mainly concerned with baseband codes. First the paper will introduce the significance and application of baseband codes research. Then comparison between unipolar and bipolar signals capabilities resisting noise will be demonstrated. Moreover, calculation of channel capacity is utilized to demonstrate the difference between NRZ and RZ waveforms. After four kinds of waveforms, they are matched into groups and contrast them in frequency domain. Lastly, few common baseband waveforms are generated so that the discussed factors application can be illustrated more vividly. The thesis is to illustrate fundamental theories more reasonable and figurative.
Improved SSOR-based signal detector by using based on gauss-seidel method for large-scale MIMO systems
Authors: Duan Chengjun
Published: July 2023

As the core technology in large-scale MIMO system, the reliability of signal detection has an important impact on the whole system. Traditional linear detectors, such as the zero-forcing (ZF), often involve very complex matrix inverse calculations when the number of antennas in large-scale MIMO systems is too large. In this paper, we first introduce the traditional signal detector based on SSOR method, the iterative operation is used to replace the complex matrix inverse calculation, thus reducing the computational complexity. Then, the Gauss-Seidel method is proposed to calculate the initial iteration value, and the simulation results show that the bit error rate (BER) performance of the improved SSOR method is greatly improved.
Review on common algorithms in path panning and improvements
Authors: Li Xinyi
Published: July 2023

Based on the cooperation of artificial intelligence (AI) and unmanned driving technology, finding the best path from the starting node to the target node in the shortest time is a research hotspot. The required path planning algorithms can therefore be classified according to their different approaches to solving the problem. This paper focuses on Dijkstras algorithm, A* algorithm, Ant colony optimization, and genetic algorithm. It also discusses the present problems of these algorithms and some improvements made by researchers focusing on automated guided vehicle path planning.
Style transfer with VGG19
Authors: Lang Langtian
Published: July 2023

Style transfer is a wide-used technique in image and photograph processing, which could transfer the style of an image to a target image that has a different content. This image processing technique has been used in the algorithms of some image processing software as well as modern artistic creation. However, the intrinsic principle of style transfer and its transfer accuracy is still not clear and stable. This article discusses a new method for preprocessing image data that uses feature extraction and forming vector fields and utilizing multiple VGG19 to separately train the distinct features in images to obtain a better effect in predicting. Our model could generate more autonomous and original images that are not simply adding a style filter to the image, which can help the development of AI style transfer and painting.
Residual H-Net: A high-level feature extraction approach for brain lesion segmentation
Authors: Song Kefan , Sun Yi , Wang Lincong , Xue Yuqiao
Published: July 2023

In the case of acute stroke patients, mere diagnosis falls short, and segmentation is needed. Recent development in deep learning and image processing has provided us with the potential to automatically perform brain lesion segmentation. However, many of the approaches ended up failing to generalize to new data by overfitting the ATLAS R1.2 dataset and ignoring information extraction of the high-level features. We propose a novel Residual H-Net that addresses these two issues by adding a special residual block in the middle of the U-Net and increasing dilation size to better extract the high-level features. The presented model is less susceptible to overfitting and much easier to train. The Residual H-Net is tested on a subset of ATLAS R2.0 data and shows promising performance against the previous state-of-the-art model.
Application and development prospect of AI speech recognition technology
Authors: Jiang Tianyu
Published: July 2023

In our daily life, artificial intelligence technology has penetrated all aspects, for us, language communication is a kind of media, but also an important way for us to convey ideas and give orders, so now, language communication has become an important way for us to interact with artificial intelligence. This paper through social research and the use of voice command to the existing speech recognition technology products test method puts forward the current development problems and solutions, the current situation of artificial intelligence speech recognition technology and the future in the field of communication systems and the intelligent home application made a simple introduction.
BP-algorithm based on factor diagram about massive MIMO system
Authors: Ling Jiaqian
Published: July 2023

In order to meet the growing demand for high-speed mobile data business, there has been a constant concern for the fifth-generation mobile communication system. 5G large-scale Multiple Input Multiple Output (MIMO) technique has significantly improved the system spectral efficiency and energy efficiency. In order to study the signal detection method under the large-scale MIMO system and improve the existing methods, the article describes the background of signal detection. It introduces the development of the belief propagation (BP) algorithm. There are four main BP algorithms: Original-BP algorithm, RDF-BP algorithm, EBRDF-BP algorithm, and GAI-BP algorithm. One algorithm is proposed based on these fundamental algorithms to improve the whole detection performance. This algorithm reduces complexity while not increasing the error rate too much, which means that it has certain feasibility and practicability.
Understand the working of Sqoop and hive in Hadoop
Authors: Uriti Archana , Yalla Surya Prakash , Anilkumar Chunduru
Published: July 2023

In past decades, the structured and consistent data analysis has seen huge success. It is a challenging task to analyse the multimedia data which is in unstructured format. Here the big data defines the huge volume of data that can be processed in distributed format. The big data can be analysed by using the hadoop tool which contains the Hadoop Distributed File System (HDFS) storage space and inbuilt several components are there. Hadoop manages the distributed data which is placed in the form of cluster analysis of data itself. In this, it shows the working of Sqoop and Hive in hadoop. Sqoop (SQL-to-Hadoop) is one of the Hadoop component that is designed to efficiently imports the huge data from traditional database to HDFS and vice versa. Hive is an open source software for managing large data files that is stored in HDFS. To show the working, here we are taking the application Instagram which is a most popular social media. In this analyze the data that is generated from Instagram that can be mined and utilized by using Sqoop and Hive. By this, prove that sqoop and hive can give results efficiently. This paper gives the details of sqoop and hive working in hadoop.
Analysis of increasing channel capacity of MIMO communication system by vortex electromagnetic wave
Authors: Jiang Jierui
Published: July 2023

Multiple-input and multiple-output (MIMO) communication technology which depends on multipath reflection can bring more efficient use of spectrum and higher channel capacity without expanding the bandwidth. This technology has been widely used in 5G communication system these days. However, under some circumstances which are lack of multipath reflection, the performance of traditional MIMO communication is not satisfying. Therefore, some researchers have pointed out that the technology of vortex electromagnetic wave can improve this situation efficiently. This article has done some researches on analyzing the channel capacity in traditional MIMO system and the MIMO system with vortex electromagnetic wave. Firstly, the spatial channel geometry model has been established with a 4-antenna transmit array and a 25-antenna receiving array in a three-dimensional rectangular coordinate system. In order to obtain the total channel capacity, the Los channel fading matrix should be calculated through calculating the distances between each two transmit and receiving antennas. After that the water filling algorithm has been used to decide the power allocation method to each subchannel to get the maximum capacity of the system. Finally, the relationship between maximum channel capacities and the signal-noise ratio (SNR) can be plotted as a line chart. The experiment first compared the capacities with and without the vortex electromagnetic wave of MIMO communication system under different SNR and found that the adding of vortex electromagnetic wave can increase the capacity efficiently. Next the influences of some variables to the channel capacity include the height of transmit antenna array, the distance between each two nearby transmit antenna elements and the variable Q which can change the phase complexity of wavefront have been discussed.
The Polyas Random Walk Theorem
Authors: Lu Jingyi
Published: July 2023

Since there are a variety of uncertainties and probabilities in the actual world, mathematicians and other researchers have found numerous answers to these common problems. They have also developed theories, such as the probability theory, to help them organize their significant discoveries. A drunk person will eventually find their way home, but a drunk bird might never find it, as said by Shizuo Kakutani. A random walk, in its most basic definition, is just a path on a network or lattice where each step is decided at random using some probability distribution, such a coin or fair dice. A motion, such as going left or right on a number line or up or down on a plane, would correspond to each outcome of tossing a coin, heads or tails. Recurrent random walks are those that end up back at the beginning after a predetermined number of steps. Any non-recurrent random walk is transitory.
Analysis of MEMS sensor application and prospects
Authors: Na Xineng
Published: July 2023

The development trends in modern science and technology are miniaturization, integration, and intelligence. Microsensors have developed rapidly with the development of micro-electromechanical systems (MEMS) and micromachining technology. In this paper, the concepts and types of MEMS sensors are summarized by literature and case analyses, and their research statuses and application fields are briefly introduced. The development trends of MEMS sensors are discussed. This paper finds that combining sensors with intelligent products can achieve another application climax of MEMS sensors.
A research agenda of AI-based analog circuit fault diagnosis with bibliometric analysis
Authors: Zhou Jingyi
Published: July 2023

Analog circuit fault identification is crucial for preserving regular operation. Methods based on artificial intelligence (AI) provide excellent accuracy in fault identification. AI-based techniques have been used widely in recent years, displaying remarkable variety and complexity. Therefore, in order to have a clearer understanding of the issues in this area, it is necessary to summarise and classify the techniques. In this article, various AI-based fault detection techniques are displayed, and bibliometrics is used to show the trend and citations. The relationships, significant writers, and journals will first be discussed in this article, after which some key pieces of literature will be displayed. The key findings and conclusions, clarification of the current issues, and a summary of the present and foreseeable research trends are all included in the last section.
Research and application of artificial intelligence in disease prediction
Authors: Bi Aoxiang , Han Ziqi , Zha Yue
Published: July 2023

Now, more and more diseases can be predicted by AI algorithms or early disease prediction, enabling patients to prepare for two kinds of physics. Because the utilitarian model of disease prediction is crucial for mankind to advance in medicine. We consider SVM(Support Vector Machine), random forest and neural networkCNNto be the proper methods to do the prediction based on the symptoms of Four diseases. SVM and Neural Network show better accuracy in the training. However, Random Forest has a slightly lower accuracy. We hope our method can be helpful in AI field.
Analysis of user behaviour and willingness regarding food waste and related products
Authors: Li Mingshuo
Published: July 2023

Food waste is not a rare problem in every days life. Food waste can cause a variety of problems such as economic loss, environmental damage, and impact on human health. Whats more, food waste has a huge market value worldwide and the list of related products is endless. Therefore, food waste is a highly valuable area to study. This research studied user behaviour and willingness regarding food waste and related products by using various methods of user research including interviews, questionaries, empathy map, key observation. Centered around user behaviour and user experience, there are a logic diagram of user behaviour, a user model, a map of user needs, an empathy story and a design frame which were built. These results are powerful tools when during design process of products related to food waste, and they can help designers to understand and develop the user empathy. Therefore, the understanding of empathy can lead to better products with more developed human care.
Applications of UAV in the agriculture field
Authors: Akshay Raikanti , Reddy Nithineshwar , Nidhi Sai Sri , R. Vijay Anand
Published: July 2023

As the world population is increasing day by day, the rise in food production becomes very crucial. Increasing prominence of technology in the agriculture sector is the X-factor to use unmanned aerial vehicles (UAVs) for the betterment of agricultural processes. In the agriculture sector, many aspects which are not under the control of human beings can also be monitored, managed by the use of technological devices like Unmanned aerial vehicles. Parallel, controlling the pollution in the environment is also important. Fertilizers and pesticides should be applied only in the appropriate amounts. Under amount leads to improper growth of the crop and over amount leads to the soil pollution which further results in water pollution. The usage of the unmanned aerial vehicles in the agriculture sector is a very beneficial thing in both aspects of crop growth and nature conservation. Advantages and application of the unmanned aerial vehicles are properly analyzed in the study.
Ways to improve user experience of visual impaired groups by accessible design in website-an example study on three educational websites
Authors: Wang Hanwen , Chen Yinming
Published: July 2023

With the popularization of the concept of equality, people begin to think more about how to let the disabled keep pace with normal people. For example, they should have the same right and access to the same public resources. The Internet, as a useful tool, helping people get rich information, and becomes more and more widely applied. Therefore, the screen reader is designed to help the special groups to receive information on the websites. However, there are still lots of websites that the disabled can't get access to, feeling pain with it, mainly because the website designers do not take accessibility into account while building. In this study, by finding the habit which visually impaired people like to surf the internet, what the massive websites' layouts are like, where the parts are that lead to the confusion the visually impaired people have, then building up an example website, which is for visually impaired students to upload their assignments, to show what an accessible website should be like, finally determining the importance of accessibility for a good website design.
SECDED code and its extended applications in DRAM system
Authors: Zhou Haochen
Published: July 2023

SECDED code is the combinational logic for communication of data between microprocessors and memories which is commonly used in semiconductor systems due to its advantage in implementation. With advances in semiconductor integrated circuit technology, the soft error rate and importance of selecting optimal codes increase. This paper presents SECDED codes and their major expansion theoretical application and gives suggestions for optimization needs.
Image recognition system based on deep learning technology
Authors: Lin Zetai
Published: July 2023

In recent years, people have been able to easily obtain a large amount of visual information through various devices, but not all of these visual information are useful, and there is a lot of useless information mixed with them, which makes it difficult for people to identify and track the target parent in the picture. Due to its various characteristics, deep learning technology can quickly obtain information from massive information and compare, analyze and utilize it, so it has become the key to solving the problem of image recognition and tracking. This paper will summarize the existing literature, focus on the structure of the image detection system based on deep learning technology, explain its basic principles, and briefly introduce the basis of deep learning technology - neural network. This paper finds that there are many technical routes for image recognition systems based on deep learning technology, each of which has its own advantages and disadvantages.
Noise signal review and analysis on a digital accelerometer in a real-world circuit system
Authors: Fang Yizhou
Published: July 2023

In recent years, the applications of MEMS inertial sensors have expanded significantly. The majority of applications challengesthe accuracy, stability, and sensitivity of inertial sensors. Noise characteristic is a crucial performance indicator for sensors. though diverse methods for analyzing and classifying sensor noise from various perspectives are proposed, t his study examines a prominent noise analysis technique known as Allan Variance (AVAR). According to the results of several computations, this approach classifies inertial sensor noise into five groups. In addition, a set of algorithms are proposed to minimize noise in order to limit sensor noise's impact on the system. In general, these algorithms disregard the type of noise and assume that it is random. In this paper, a quick introduction to these algorithms will be provided. A comprehensive investigation of accelerometer noise will conclude this paper. The noise signal is gathered under various conditions for comparison. Typically, this research illustrates a potential difficulty with microcontroller noise signal reception accuracy. The impact and potential explanation of such a problem on noisy signal reception will also be discussed.
Comparison of deep-learning and conventional machine learning algorithms for salary prediction
Authors: Feng Ziyuan , Liu Zixian , Yin Yibo
Published: July 2023

Salary is an integral part of contemporary life. With the large-scale use of machine learning, it has become possible to predict salaries with machine learning. Previous researchers have used random forest algorithms to solve this problem, however, there is a research gap in using a neural network to solve this problem. Therefore, the research topic of this paper is to use convolutional neural networks (CNN) and datasets on Kaggle to predict salary. The research methodology of this paper is as follows. First, the Kaggle dataset is divided into the train-dataset and the test-dataset. After preprocessing the data, two kinds of features are obtained. The features will be transformed into two two-dimensional matrices. Next, the matrices were used to train two CNNs separately. These two CNNs will be connected together to get the predicted salary by fully connected layers and Relu activation functions. After training the CNN, the study called the test dataset to verify the accuracy of the model. Similarly, the study used a random forest model for prediction. Finally, the comparison of the two results showed which algorithm was better. The study found that the error rate of the CNN was 0.0732 and its variance was 0.1899. The error rate of the random forest was 0.2437 and its variance was 0.8285. From the results, CNN is better than random forest in terms of accuracy and stability. Therefore, using CNN for salary prediction has a high probability of getting better results.
The application of ultrawideband technology in future wireless communications and practical exploration
Authors: Ren Yuanchao
Published: July 2023

An innovative form of wireless communication technology is called ultra-wideband technology. By directly modulating impulse pulses with extremely rapid rise and fall times, it is possible to create signals with bandwidths of the order of GHz. It has the benefits of being insensitive to channel fading, low power spectral density of the transmitted signal, low interception capability, low system complexity, and the ability to provide several centimeters of positioning accuracy. It also resolves the main propagation issues that have plagued traditional wireless technology for many years. Early high-speed data transmission in close proximity utilised ultra-wideband; more recently, foreign nations have started using its sub-nanosecond ultra-narrow pulse for close-range indoor positioning. Traditional wireless communication modulates signals to various frequency bands using various carrier frequencies, and within a given range, the carrier wave's frequency and power will change. Ultra-wideband wireless communication does not require a carrier wave, but uses pulsed signals to transmit information, where pulsed signals are those that are generated and disappear in a very short time, from a few hundred microseconds to less than a few nanoseconds. Thirdly, it can be positioned with high accuracy and has good resistance to multipath effects in timing. Ultra-wideband technology wireless communication systems generally work at sub-nanosecond pulse widths, and thus have sub-nanosecond time resolution, and its multipath resolution is correspondingly less than 30 cm, the signal will be received in the formation of a 1-nanosecond time reception window, only receive the signal within the reception window, the multipath interference has very good resistance. Fourthly, it has a greater penetration capability. Ultra-wideband pulses have a low frequency, the lowest of any wireless signal with the same absolute bandwidth, so they have greater penetration capability. Fifthly, the structure is simple, and the cost is low. The wireless communication system of ultra wideband technology does not change the traditional carrier wave to realize information transmission. The wireless communication system uses up conversion circuit, down conversion circuit, intermediate frequency circuit and various filters. The system structure is simple, and communication is relatively tolerant and easy. Therefore, the cost of wireless communication using ultra wideband technology is much lower.
Prediction of the price of used cars based on machine learning algorithms
Authors: Zhu Yian
Published: July 2023

The used car market is really huge, being caused by a variety of reasons, so it matters to forecast the transaction price of used cars. The study can help people make a better choice when they are willing to purchase a second-hand car. Machine learning is the most effective tool for predicting things at present, and thats why machine learning models are chosen to realize the study. Three machine learning models are involved in the study, SVM, XGBoost and neutral networks. The predictive effect on used car prices is evaluated with accuracy and precision. In the end of the study, the results of the three models are compared with each other, and then a model with a best effect of prediction will be selected. The result of the comparison shows that SVM performs best in the study of used car transaction price forecast. The models used in the study are comparatively shallow, so perhaps some more advanced models will be added to the project in the future.
Resume recommendation based on text similarity
Authors: Dong Zhenyu
Published: July 2023

With the vigorous development of the mobile Internet era, traditional offline recruitment methods are gradually fading out of people's sight. Internet recruitment has become the first choice of many job seekers and companies due to its advantages of low cost and high efficiency. However, suitable positions for job seekers and resume information for recruiters are often drowned in a sea of information. How to find an effective resume recommendation algorithm is still an open issue. To this end, this paper proposes a personalized resume recommendation method based on text classification. Specifically, by encoding and extracting the feature information of different resumes, and scoring the matching degree between job seekers and job information based on the XGBoost algorithm, personalized job information recommendations are made for job seekers. A large number of experiments have verified the effectiveness of the method in this paper, which can provide new insights for the efficient matching of resumes and job information.
Synthetic aperture radar radio frequency interference suppression technology
Authors: Wu Zekai
Published: July 2023

Radio frequency interference (RFI) can easily hinder the data collection, imaging and interpretation of the initial echo of synthetic aperture radar, which has always been a difficult problem affecting the accuracy of synthetic aperture radar. In this paper, the radio frequency interference suppression technology of synthetic aperture radar is analyzed and studied. It can be concluded that in todays complex and changeable electromagnetic environment, although many literature have proposed and established different objective functions and constraints for more specific application environments, there is still room for further improvement. Therefore, the future SAR system needs to select the most appropriate interference suppression method according to the dynamic changes of RFI environment. The development trend of interference suppression technology in the future is obtained from the comprehensive analysis of the RFI interference sources, RFI models and existing SAR interference suppression technologies, which provides a certain reference for future research.
Requirement of Strong Legal Framework and Procedures to Contest with Cybercrime in Pandemic Situation
Authors: Dr Aftab Ahmad Malik  , Mujtaba Asad  , Dr Waqar Azeem
Published: July 2023

One of the most significant global occurrences in recent history will be the COVID-19 pandemic in 2020. The government's response to issuing legal stay-at-home orders is one facet of this situation that is unique. COVID-19 has affected the world in several ways not seen in decades. One of the effects is crime rates, which appear to have fallen in some communities around the world. We argue that the government's order to stay at home may be the principal reason for the change. While in some other countries, there has been an increase. In fact, the impact has been different in different ways. The important question is how the effect on the rate of crime will be in the future; increase or reduction. The tendency of crime regarding torturing, abusing, molesting, assaulting, raping, or killing innocent women and children increased. Pakistan formulated fresh legislation. The major role in combating the crime depends upon the existence of strong legislation capable of causing a reduction in the crime rate, which allows the investigators vast powers and collaboration with the prosecution and safeguarding the witnesses. The criminals are very well organized and use the most modern technology and IT equipment, therefore, the police, investigators, and prosecutors must have and be highly trained and equipped, similarly. No strategy can be successful in the absence of strong legislation. The criminals involved in Cybercrime and white-collar crime keep on acquiring and hacking the data of people, government, and business organizations by crossing security barriers of computers and networks. The occurrence of crime increased particularly in threats to attack and asking for money to stop the attack. More strict security measures must be adopted to safeguard the data and networks and strong encryption attained and implemented. The European Union advocates focusing on a strong legal framework. In addition, there exist justifications to amend the US cyber legal framework to reduce the frequency of crime. The paper presents some salient legal, procedural, and feasible measures. The most salient philosophy presented in this research paper is that there must exist strong legislation coupled with morality, a code of ethics, and severe punishment as deterrent forces to combat these offenses.
Role of Legislation, Need of Strong Legal Framework and Procedures to Contest Effectively with Cybercrime and Money Laundering
Authors: Dr Aftab Ahmad Malik  , Dr Mujtaba Asad  , Dr Waqar Azeem
Published: July 2023

There is need for a robust and strong legislation to tackle white Collar-crime is stressed, which is on the rise in both the public and private sectors. The effect of immoral and unlawful actions in government, notably high-level bribes, has crippled the financial and legislative bodies in their normal functioning. Bank frauds, money laundering, and cybercrimes are also on the rise, due to the widespread use of digital gadgets and the internet. The absence of strong network-security systems especially in the banking sector has caused great losses indeed. The goal of this study is multidimensional; more about the importance of applying strong regulations as well as morality and ethical principles. It has been argued in this paper that morality and ethical norms positively influence minimizing such crimes; if morality and ethics are coupled with strong legislation, it works as a Deterrence Force. It will undoubtedly be one of the most momentous global occurrences in recent history, long-term impacting culture, government operations, crime, economics, politics, and social relationships. The major role in combating the crime depends upon the existence of strong legislation capable of causing a reduction in the crime rate, which allows the investigators vast powers and collaboration with the prosecution and safeguarding the witnesses. The criminals are very well organized and use the most modern technology and IT equipment, therefore, the police, investigators, and prosecutors must have and be highly trained and equipped, similarly. appropriate methods and algorithms are required. We create a new method, a dynamic atomic shared memory for message communication. A properly stated method is proposed for message communication and then implemented. According to this method, owners can be changed dynamically, and their access to read and write also changes.
Malware and their diverse characteristics related to detection and analysis: A literature survey
Authors: Muhammad Taseer Suleman
Published: July 2023

The term malware refers to a specific form of software that causes damage to the computing device through data leakage and transformation, device malfunctioning, hacking, and exploitation. Typical malware can be categorized into several categories including viruses, worms, trojans, ransomware, etc. The analysis of malware helps in the categorization and behavior judgment of malware. The deep analysis of malware helps in malware detection. The current research study covers a hierarchical representation of various malware categories, different forms of detection, computing devices for malware, and a malware analysis approach. The study describes each category in detail, which helps in forming the mapping of malware analysis in detail.
A Review of Cyber Security and Cyber-Attacks – What to Know?
Authors: Malik Muhammad Shairoze
Published: July 2023

In this era, human activities have seen a shift and our majority activities including social, cultural,economic and even governmental and NGOs are being done in the cyberspace, especially during andafter the crisis of corona pandemic. Due to this shift in communication culture, many individuals andorganizations including governments have to face cyber-attacks. Due to heavy reliance ontechnology and little awareness, defending against cyber-attacks is very challenging. Cyber attacksare usually conducted with the goal of harming an organization or individual financially or theseattacks may also be motivated for political or military purposes. Viruses, malwares, ransomwares,denial-of-service and phishing attacks are some of the examples. To protect themselves,organizations employ variety of strategies to mitigate or prevent the threat of these attacks. Toprevent and mitigate cyber-attacks, researchers and professionals have devised a number oftechniques. This paper is written to thoroughly study and analyze these various approaches andproposed cybersecurity standards, and also to look into the problems, limitations and strengths ofthese techniques. Fundamental concepts of cyber-attacks and cyber security are discussed alongwith the current advancements and upcoming trends in security of cyber space. Such acomprehensive review paper would be highly beneficial.
IMPLEMENTATION OF VIRTUAL REALITY IN SIMPLE MATH QUIZZES AS A CHILDREN'S LEARNING PLATFORM
Authors: Ridloka Danief , Cahyani Vivy , Zuama Hatta , Hidayat M. Mahaputra
Published: July 2023

Virtual Reality (VR) has been used extensively in various fields, including education. This study aims to implement VR in simple math quizzes as a medium for children's learning. The purpose of this study is to increase children's interest and motivation in learning mathematics and improve their problem-solving skills. This research uses software development methods, which consist of several stages, namely needs analysis, design, development, evaluation, and revision. The result of this study is software that allows children to interact with mathematical material in an engaging VR environment. This research shows that the use of VR in mathematics learning can increase children's interest and motivation in learning and improve their problem-solving skills. It is hoped that the results of this research can make a positive contribution in the development of mathematics learning that is more interactive and fun for children.
Especies vegetales del Área de Conservación Municipal y Uso Sostenible Numbala, Palanda, Zamora Chinchipe, Ecuador
Authors: Jaramillo Díaz Nelson , Pinta Pineda Gabriela , Luzón Jirón Daniel , Aguirre Mendoza Zhofre , Martínez González-Quevedo Jennifer , Mendoza Franco , Días Jhuly , Lima Robinnson
Published: July 2023

En mayo 2023 la Fundación de Conservación Jocotoco Ecuador en cooperación con el Herbario "Reinaldo Espinosa" -LOJA-, de la Universidad Nacional de Loja, realizaron la expedición botánica en el Área de Conservación Municipal (ACMUS) Bloque 3, en los bosques ubicados en la parte alta del Filo del Águila y Cordillera de San Francisco, cantón Palanda, provincia de Zamora Chinchipe, cuya formación vegetal corresponde a  Bosque siempreverde montano del Sur de la Cordillera Oriental de los Andes; con el propósito de recolectar, identificar y registrar los diferentes taxones florísticos de esta zona. Para lo cual, el equipo técnico del Herbario registró información de la diversidad florística, especies endémicas, amenazadas, registros nuevos para la ciencia, realizando la identificación de las especies y el registro fotográfico de las especies, con un total de 23 especies epífitas, 31 arbóreas, 20 arbustivas, 6 enredaderas-trepadoras y 3 especies de palmas; lo cual contribuirá al conocimiento científico importante para formular estrategias y tomar decisiones de conservación.
IMPLEMENTASI METODE DOUBLE DIAMOND DALAM PERANCANGAN PROTOTIPE APLIKASI SISTEM ERP BERBASIS WEBSITE
Authors: Jauhari Muhamad Thanthawi , Prayudi Yudi
Published: July 2023

Setiap perusahaan memiliki kebutuhan untuk memiliki sistem yang dapat mendukung proses bisnisnya, seperti sistem enterprise resource planning (ERP). Ada dua varian sistem ERP, yaitu tradisional dan modern. Namun, banyak perusahaan yang belum mengadopsi sistem ERP karena keterbatasan sumber daya manusia yang mampu mengembangkan sistem internal atau biaya pembelian software dari pihak ketiga. Hal ini mengakibatkan waktu yang terbuang dalam koordinasi dan kinerja perusahaan sulit untuk ditingkatkan. Sebagai solusi, pengembangan aplikasi sistem ERP berbasis website dengan mengoptimalkan kemajuan teknologi dan menggunakan kerangka kerja double diamond dalam perancangan desainnya menjadi alternatif. Double diamond adalah kerangka kerja desain yang digunakan dalam proses inovasi dan pengembangan produk atau layanan. Dalam double diamond, terdapat empat tahapan utama: menemukan, mendefinisikan, mengembangkan, dan mengantarkan solusi yang optimal. Sehingga dari penelitian ini dapat membuat alur dan proses bisnis perusahaan semakin optimal dan efisien.
Aplicación del Principio del trabajo Virtual en la obtención de la respuesta estructural de pórticos isostáticos
Authors: Guzman Miguel
Published: July 2023

Este trabajo de investigación tiene como finalidad determinar la respuesta estructural de un pórtico isostático sometido a distintos sistemas de carga, mediante el método de la carga unitaria y el software SAP2000, con ello obtener qué efectos aportan más hacia la deflexión, de igual manera para desplazamientos horizontales afectados por temperatura, el alcance es descriptivo-comparativo con una metodología de investigación descriptiva, donde se obtuvo que la deflexión por el software SAP2000 y el PTV tiene una variación de 0.006347%, siendo un margen de error despreciable, además el aporte del efecto por deformación axial y cortante tiene una influencia mínima del 0.01385% siendo el efecto de la deformación por flexión el predominante con un 99.98614%, para el desplazamiento horizontal afectado por temperatura, a través del software SAP2000 y PTV, se obtuvo un margen de 0.0054% que no es significativo, donde los aportes relevantes hacia el desplazamiento horizontal fueron los efectos de deformación por flexión y axial, con un aporte de 95.5962 % y 4.4038 % respectivamente. Por tanto, se concluye que por medio del PTV y el software SAP2000, los desplazamientos horizontales y verticales tienen una variación no significativa, por otro lado, para obtener una deflexión se considera solo el efecto de deformación por flexión, y para un desplazamiento horizontal afectado por temperatura se analiza tanto el efecto por deformación axial y flexion.
Penentuan Dosis Pupuk Berdasarkan Data Tonase Tandan Buah Segar (TBS) pada Perkebunan Kelapa Sawit
Authors: Tjandra Winaldo , Ginting Candra , Gunawan Sri
Published: July 2023

The productivity of Fresh Fruit Bunch (FFB) in Indonesia is relatively low with an average productivity of below 15 tonnes.ha-1.year-1,which is still very far below its potential, which is around 25 tonnes.ha-1. year-1, one of the contributing factors is the application of fertilizers. neither the type nor the dose has been done precisely. Research on Determining Fertilizer Dosage Based on FFB  tonnage data for oil palm plantations has been carried out from March to October 2022 at a private oil palm plantation company located in Nunukan Regency, North Kalimantan Province. The research was carried out on an area of ​​812 ha which was divided into 28 blocks, consisting of 7 treatments each carried out in 4 blocks as repetition. The soil pH conditions are relatively neutral, namely between 6.0-6.9. Fertilizers used are also of various kinds, namely Urea, Rock phosphate, Muriate of potash, Kieserit and Dolomite. The dosage of fertilizer is determined based on the tonnage of fresh fruit bunches produced and compared with the dose of fertilizer according to the recommendations from the leaf sampling unit. This study uses monthly data for each block from March to October 2022 which includes: average stem weight (BJR), number of stems per tree (JJG/PKK), and productivity (tons.ha-1.month-1). The data obtained were then analyzed for variance and continued with Duncan's multiple range test. The results showed that in March, April and October there was a significant difference between the treatments where in March there was a difference in the productivity of fresh fruit bunches where the application of Urea-Rph-MOP-Kieserite fertilizer was 4.3-2.5-1 respectively. .9-2.9 respectively in kg.principle-1.year-1 (P1) shows the highest productivity. In April and October there was a significant difference in the yield per tree where in April the Urea-Rph-MOP fertilizer application treatment was 2.4-1.6-1.8 respectively in kg.principal-1 year-1 (P5) showed that the number of shoots per tree tended to be higher than the other treatments, whereas in October the number of stems per tree tended to be higher in treatment P1. However, there was no significant difference in average length weight from March to October. Thus the dosage of fertilizer can be determined based on fresh fruit bunch tonnage data as an option other than based on the results of leaf sampling units to be implemented in the field.
Analysis of Key Attributes of Wooden Toys via an Interval-Valued Spherical Fuzzy Analytic Hierarchy Process
Authors: Singer Hilal , Özşahin Şükrü
Published: July 2023

The evaluation of wooden toys is a complicated process and can be overwhelming for decisionmakers in the presence of many conflicting criteria. Hence, this study proposes a fuzzy decision-making model to identify and prioritize the key attributes of wooden toys. For this purpose, the interval-valued spherical fuzzy analytic hierarchy process (AHP), which is one of the fuzzy multicriteria decision-making methods, is applied to obtain weight vectors. Firstly, the wooden toy evaluation problem is formulated as a multicriteria decision-making problem. Then five main criteria and twenty subcriteria are defined with the help of experts. The decision-making team carries out the pairwise comparisons of the criteria. As a result, the priority weights are computed and the ranking order of the criteria is revealed. Additionally, the validity of the obtained results is supported by conducting a comparative analysis between other popular fuzzy methods: interval type-2 fuzzy AHP, interval-valued Pythagorean fuzzy AHP, and spherical fuzzy AHP. According to the modeling results, the most important criteria are “absence of small parts and sharp edges”, “free of harmful wood preservatives and paints”, “workmanship quality”, “contribution to psychomotor development”, and “contribution to cognitive development”. The proposed framework can be adapted to similar decision processes for the evaluation or improvement of toys. Consequently, the findings of this research will help manufacturers, designers, and consumers in making conscious decisions.
Network Management Model for Device-To-Device Communication in Ultra Dense Mobile Networks
Authors: Logeshwaran J. , Kiruthiga T.
Published: July 2023

This paper proposes a novel context-based network management model for device-to-device (D2D) communication in ultra dense mobile networks. Network management activities, such as bandwidth allocation, interference control, mobility management, resource management, and security management are addressed. To this end, a two-tier structure consisting of a context-aware device layer in the radio access network (RAN) and a centralized application layer is presented. The respective roles of these layers in the management model are discussed in detail. In particular, the context-aware device layer focuses on providing information regarding the application layer, while the application layer is responsible for monitoring of the overall D2D network. Additionally, a resource-efficient management scheme is proposed, based on the context-aware device layer, in order to optimize the bandwidth allocation in the D2D network. This kind of management model allows for the network to be used more effectively in ultra dense mobile systems, as it effectively offloads data traffic from classical cellular systems. Finally, the performance of the proposed network management model is evaluated through simulations.