bluuebunny/crossref_metadata_2025 huggingface dataset:
Maharashtra Rainfall Prediction using Machine Learning
Authors: Prof. T. P. Raju  , Tejeswini Naidu  , Herambh Jatadhar  , Shraddha Manerao  , Ashish Armarkar
Published: August 2023

Machine learning is the foundation of the attempt to predict rainfall. Here, our research will use historical data analysis to forecast rainfall. In this research, a genetic algorithm is utilized. Various researchers are doing a wide range of studies to forecast rainfall before it really occurs. The usage of genetic algorithms has been heavily utilized for a variety of research projects, and weather prediction is no different. With the use of genetic algorithms, we have created a system in this study that could anticipate rain. Genetic algorithm is used to extract features from the input data set. When compared to other approaches use of genetic algorithms seems to be more efficient for predicting the rainfall as hence it is used in the current work. The evaluation results are performed based on evaluating various parameters and the proposed model seems to provide a better efficiency when compared to the rest of the previous traditional rainfall prediction systems
The Impact of Artificial Superintelligence: Blessing or Curse
Authors: Pranjali Amalkar
Published: August 2023

The development of artificial superintelligence (ASI) has sparked intense debates and discussions about the potential consequences for humanity. It is essential to evaluate both ASI's benefits and drawbacks because its capabilities exceed those of the average person. The goal of this paper is to offer a thorough examination of the varied aspects of ASI's impact. This study aims to shed light on the tremendous consequences that ASI could have for our world by exploring a wide range of perspectives, ethical conundrums, economic transformations, and potential societal alterations. I explore the potential advantages of ASI in this work, including its ability to change scientific discovery by analyzing massive datasets and producing hypotheses. Additionally, the potential contributions of ASI to the healthcare industry are looked at, including tailored treatment and broadened diagnostics. The report also emphasizes how ASI-driven automation may transform labor markets by obviating routine chores and freeing up human beings to work on innovative and strategic projects
Avaliações de produções científicas: desafios e motivações de editores e avaliadores
Authors: Guedes Farias Maria Giovanna , Santos Gildenir Carolino
Published: August 2023

Objetivo: Esta investigação teve como foco compreender os desafios e motivações de editores e avaliadores, no processo de avaliação de produções submetidas a periódicos científicos.
Metodologia: Para tal, conduziu-se esta pesquisa por meio de aporte metodológico focado na abordagem qualitativa, com uso do método de pesquisa exploratória e de questionários direcionados a avaliadores e a editores de periódicos da Ciência da Informação e da Educação, a fim de coletar dados a serem tratados por meio da análise de conteúdo com o estabelecimento de categorias. 
Resultados: Os resultados demonstram que a maioria dos editores e avaliadores, respondentes desta investigação, é experiente na percepção do trabalho editorial, e que no Brasil os envolvidos com a editoração científica são voluntários, e ainda pouco reconhecidos por méritos acadêmicos.
Conclusão: Conclui-se que, com a complexidade, relevância e as controvérsias em torno do processo de avaliação, o qual envolve todos os atores da produção científica (editores, avaliadores e autores), talvez essas experiências de papéis ajudem na compreensão da necessidade de um parecer bem elaborado e em tempo hábil, mas também, deveriam contribuir para que as diversas ações sugeridas pelos sujeitos da pesquisa, fossem realmente colocadas em prática, colaborando para o desenvolvimento da ciência e da comunidade científica.
Sistem Pakar Diagnosa Penyakit Autis Pada Anak-Anak Menggunakan Metode Fuzzy Logic
Authors: Iqbal Iqbal , Husna Asmaul
Published: August 2023

Autis merupakan penyakit akibat dari gangguan pada Otak. Banyak jenis gangguan perkembangan anak yang tidak disadari oleh orang tua. Salah satu dari gangguan perkembangan Anak adalah penyakit Autis. Variabel-variabel pendukung penegakan diagnosis penyakit tersebut digunakan dalam pembentukan himpunan fuzzy. Himpunan fuzzy itu akan menghasilkan suatu keputusan yang pasti. Adapun maksud dari penelitian skripsi ini adalah membangun sebuah sistem pakar yang mampu untuk mengambil keputusan diagnosa penyakit sesuai dengan pengetahuan Pakar atau Dokter. Sedangkan untuk alat pengembangan sistem pakar menggunakan bahasa pemongraman Php dan MySQL. Aplikasi yang dirancang telah diuji dengan melibatkan rekam medis diagnosa dari Dokter atau Pakar penyakit Autis pada Anak, hasil keputusan yang dihasilkan aplikasi adalah sama dengan diagnosa Dokter yang tertera di rekam medis. Secara umum aplikasi Sistem Pakar berbasis web ini bisa digunakan sebagai alat bantu atau pendamping dalam mendiagnosis penyakit Autis pada manusia tanpa harus langsung berkonsultasi secara tatap muka kepada Dokter
Penerapan Metode AHP-WP Dalam Penentuan Lulusan Terbaik Profesi Ners UMKT
Authors: Fajrul Pallah Bintang , Latipah Asslia Johar , Rahim Abdul
Published: August 2023

Profesi Ners merupakan program studi lanjutan di bidang keperawatan. Dalam menyelesaikan studinya terdapat mahasiswa lulusan terbaik yang akan dipilih. Pada pelaksanaan penentuan lulusan terbaik terdapat beberapa kriteria yang harus di penuhi, tetapi dalam pelaksanaannya masih menggunakan kriteria tertentu yang tidak objektif. Maka dari itu diperlukan suatu metode pengambilan keputusan yang dapat memperhitungkan segala kriteria yang di gunakan untuk menentukan lulusan terbaik. Berdasarkan kriteria yang telah di tentukan oleh pihak Prodi Profesi Ners UMKT dilakukan perhitungan dengan menggunakan metode AHP-WP. Metode AHP digunakan untuk menentukan bobot dari setiap kriteria, sedangkan metode WP digunakan untuk perangkingan alternatif. Dari hasil perhitungan di dapat bahwa alternatif 1 (Dinda Ayu Framaisella) sebagai peringkat 1 yang berarti menjadi lulusan terbaik. Dalam pengujian ini di diperoleh akurasi sebesar 73,40% menggunakan 94 data alternatif dari mahasiswa Profesi Ners TA 2021/2022.
Media Pembelajaran Budidaya Udang Vaname Berbasis Multimedia
Authors: Rizani Fitri
Published: August 2023

media pembelajaran merupakan satu media yang sangat aktif di dunia serba online ini. Teknologi ini adalah suatu teknik perkenalan suatu objek yang sangat banyak digunakan di bidang budidaya, Dengan hal ini teknologi media pembelajaran dapat berguna untuk membantu para masyarakat dalam mencari informasi yang lebih lengkap dan tepat tentang suatu ilmu budidaya udang vaname. Terknologi media pembelajaran tersebut dapat dikembangkan dalam bentuk video, foto maupun animasi. Dalam bidang video, teknologi media pembelajaran masih belum terlalu banyak penggunanya. Saat ini masih banyak yang menggunakan majalah dan buku sebagai sarana referensi diamana sarana ini sering membuat para masyarakat kecewa akan hasilnya. Materi yang didapatkan hanya berupa teks dan gambar. Oleh karena itu, peneliti berinisiatif untuk merancang sebuah media pembelajaran sebagai sarana edukasi dan menarik. Media promosi ini dibuat dengan menggunakan aplikasi Adobe Flash
Putz und Stuck erhalten.
Authors: Diehl Carmen , Marinowitz Cornelia
Published: August 2023

Bei vielen Bauprojekten werden historische Putz- und Stuckausstattungen unwiederbringlich zerstört und durch neue Materialien ersetzt. Grund dafür ist häufig Unsicherheit im Umgang mit den alten Baustoffen. Dass es auch anders geht, zeigt dieses Buch: Die Autorinnen geben einen Einblick in die geschichtliche Entwicklung von Putz und Stuck. Sie erklären die zur Mörtelherstellung verwendeten Bindemittel Lehm, Kalk, Gips und Zement und deren Verarbeitungstechniken. An Beispielen erläutern sie Konservierungsarbeiten an Fassadenputzen, Stuckdecken und Unterkonstruktionen.

Diese Kenntnisse und die im Buch empfohlenen Checklisten zur Bestandsbeschreibung helfen einzuschätzen, ob für eine Erhaltungsmaßnahme einfache handwerkliche Reparaturen ausreichen. Bei komplexeren Aufgaben ermöglichen sie, gemeinsam mit Spezialist:innen für Restaurierung, Denkmalpflege und Naturwissenschaften praktikable Lösungen zu finden.
Multi-Plane Neural Radiance Fields for Novel View Synthesis
Authors: Abdelkareem Youssef , Shehata Shady , Karray Fakhri
Published: August 2023

Novel view synthesis is a long-standing problem that revolves around rendering frames of scenes from novel camera viewpoints. Volumetric approaches provide a solution for modeling occlusions through the explicit 3D representation of the camera frustum. Multi-plane Images (MPI) are volumetric methods that represent the scene using front-parallel planes at distinct depths but suffer from depth discretization leading to a 2.D scene representation. Another line of approach relies on implicit 3D scene representations. Neural Radiance Fields (NeRF) utilize neural networks for encapsulating the continuous 3D scene structure within the network weights achieving photorealistic synthesis results, however, methods are constrained to per-scene optimization settings which are inefficient in practice. Multi-plane Neural Radiance Fields (MINE) open the door for combining implicit and explicit scene representations. It enables continuous 3D scene representations, especially in the depth dimension, while utilizing the input image features to avoid per-scene optimization. The main drawback of the current literature work in this domain is being constrained to single-view input, limiting the synthesis ability to narrow viewpoint ranges. In this work, we thoroughly examine the performance, generalization, and efficiency of single-view multi-plane neural radiance fields. In addition, we propose a new multiplane NeRF architecture that accepts multiple views to improve the synthesis results and expand the viewing range. Features from the input source frames are effectively fused through a proposed attention-aware fusion module to highlight important information from different viewpoints. Experiments show the effectiveness of attention-based fusion and the promising outcomes of our proposed method when compared to multi-view NeRF and MPI techniques.
Depth-Based Region Proposal: Multi-Stage Real-Time Object Detection
Authors: Ayman Shehab Eldeen , Hussein Walid , H. Karam Omar
Published: August 2023

Many real-time object recognition systems operate on two-dimensional images, degrading the influence of the involved objects' third-dimensional (i.e., depth) information. The depth information of a captured scene provides a thorough understanding of an object in fulldimensional space. During the last decade, several region proposal techniques have been integrated into object detection. scenes’ objects are then localized and classified but only in a two-dimensional space. Such techniques exist under the umbrella of two-dimensional object detection models such as YOLO and SSD. However, these techniques have the issue of being uncertain that an object's boundaries are properly specified in the scene. This paper proposes a unique region proposal and object detection strategy based on retrieving depth information for localization and segmentation of the scenes’ objects in a real-time manner. The obtained results on different datasets show superior accuracy in comparison to the commonly implemented techniques with regards to not only detection but also a pixel-by-pixel accurate localization of objects.
Amadeus Migration Process a Simulation-Driven Process to Enhance the Migration to a Multi-Cloud Environment
Authors: Romdhanne Bilel Ben , Boudia Mourad , Bondoux Nicolas
Published: August 2023

With the development of the cloud offers, we observe a prominent trend of applications being migrated from private infrastructure to the cloud. Depending on the application’s complexity, the migration can be complex and needs to consider several dimensions, such as dependency issues, service continuity, and the service level agreement (SLA). Amadeus, the travel industry leader, had partnered with Microsoft to migrate its IT ecosystem to the Azure cloud. This work addresses the specificity of cloud-to-cloud migration and the multi-cloud constraints. In this paper, we summarise the Amadeus Migration process. The process aims to drive the migration from an initial private cloud environment to a target environment that can be a public or hybrid cloud. Further, the process focuses on a prediction phase that guides the migration process. This paper expects to provide an efficient decision-making process that guides managers and architects to optimise and secure their migration process while considering micro-servicesoriented applications targeting an efficient deployment over multi-cloud or hybrid cloud. The prediction relies on the network simulation to predict applications’ behaviour in the cloud and evaluate different scenarios and deployment topologies beforehand. The objective is to predict migrated applications’ behaviour and identify any issue related to the performance, the application’s dependency on other components, or the deployment in the cloud. The migration process proposed in this paper relies on SimGrid, a toolkit developed by INRIA[52] for distributed application modelling. This framework offers a generic process to model IT infrastructure and can assist cloud-to-cloud migration. Specific attention is given to predictive and reactive optimisations. The first results show predictive optimisation's impact on securing KPI and reactive optimisation to optimise the solution cost. Thus, we reach an average cost reduction of 40% in comparaison with the same deployment strategy while keeping the same SLA.
An Energy-Efficient Tunable-Precision Floating-Point Fused Multiply-Add Unit based on Neural Networks
Authors: Sun Xiyang , Zhao Yue , Zhang Sheng
Published: August 2023

Convolutional neural networks have been continuously updated in the last decade, requiring more diverse floating-point formats for the supported domain specific architectures. We have presented VARFMA, a tunable-precision fused multiply-add architecture based on the Least Bit Reuse structure. VARFMA optimizes the core operation of convolutional neural networks and supports a range of precision that includes the common floating-point formats used widely in enterprises and research communities today. Compared to the latest standard baseline fused multiply-add unit, VARFMA is generally more energy-efficient in supporting multiple formats, achieving up to 28.93% improvement for LeNet with only an 8.04% increase in area. Our design meets the needs of the IoT for high energy efficiency, acceptable area, and data privacy protection for distributed networks.
Predicting Stock Prices Using Tweet Frequency and AI: Leveraging Social Media Insights to Forecast Tomorrow's Market Trends
Authors: Liu Zimo , Yang Lin , Takada Tami
Published: August 2023

I use the frequency of the tweet counts of the stock ticker to predict the stock price [1]. Using AI to predict the price with today’s tweet count and the highest and lowest stock price to predict tomorrow’s stock price [2]. The benefits of predicting stock prices are minimizing losses and getting a better idea about making money. But since the price of stocks is hard to predict, analyzing the number of price tickers discussed in social media can help people to know more precisely trends. “They analyzed the activity of 150 companies chosen at random from the S&P 500 Index and noticed a correlation between the number of tweets they sent and their share price [3]. Having observed this, the researchers devised a mathematical model, applied it to an imaginary portfolio and outperformed other financial strategies based on financial analysis by as much as 11%” [4]. This indicates the reliability of predicting stock prices with social media. Compared with some popular methods such as Auto-Regressive Conditional Heteroscedastic or Generalized Auto-Regressive Moving Average, using social media to predict price can consider the effect of social trends on the stock price [5]. Using social media to predict the stock price is not subjective and is much cheaper to computerize.
Exploring the Synergistic Integration of Artificial Intelligence and Dropshipping: A Comprehensive Investigation into Optimizing Supply Chain Management, Enhancing Customer Experience, and Maximizing E-commerce Profitability through AI Driven Solutions
Authors: Wang Rundong , Yang Lin , Le Patrick
Published: August 2023

The dropshipping industry presents significant challenges for entrepreneurs, particularly in product selection, website creation, and overall management of their online stores [1]. The sheer volume of products available, fierce competition, and the complexities of inventory management and customer service can be overwhelming for newcomers [2][3]. To address these issues, we propose a unique, AI-powered dropshipping platform that not only automates and optimizes essential aspects of running a dropshipping business but also offers a feature that distinguishes it from others: personalized website generation [4]. Our platform uses cuttingedge technologies such as artificial intelligence, machine learning, and data analytics to streamline operations and increase efficiency. It comprises essential components, including data acquisition via sophisticated web scraping techniques, AI analytics that use machine learning algorithms and mathematical formulas for data analysis and product performance prediction, and user interface generation, focusing on creating a user-friendly interface for straightforward navigation and informed decision-making [6]. What sets our platform apart is its ability to generate personalized websites based on the user's chosen items to dropship. This unique feature enhances advertising capabilities by offering a tailored online presence that displays selected products in an engaging and persuasive way. These generated websites are visually appealing, user-friendly, and SEO-optimized for maximum exposure, enabling better engagement with the target audience, increasing conversions, and driving sales [5]. Our AIpowered dropshipping platform is more than a tool; it's a comprehensive solution that allows dropshippers to efficiently manage their business, from product selection to website creation and advertising [7]. By enabling entrepreneurs to focus more on marketing and customer relationships, it contributes to increased efficiency and higher success rates. It satisfies the growing demand for personalized online experiences, empowering dropshippers to tailor their online stores to their specific niche or target market, thereby enhancing their branding in a highly competitive e-commerce landscape. In conclusion, our platform provides an effective solution to the challenges faced by dropshipping entrepreneurs. Its unique website generation feature, along with accurate product selection, scalability, and user-friendly interface, contribute to improved profitability, customer satisfaction, and long-term growth in the competitive drop shipping industry. The integrated approach of our solution eliminates the need for dropshippers to rely on multiple tools, thereby simplifying operations and reducing complexity, ultimately enhancing their success.
Real Time Deep Learning Weapon Detection Techniques for Mitigating Lone Wolf Attacks
Authors: Kambhatla Akhila , R Khaled Ahmed
Published: August 2023

Firearm Shootings and stabbings attacks are intense and result in severe trauma and threat to public safety. Technology is needed to prevent lone-wolf attacks without human supervision. Hence designing an automatic weapon detection using deep learning, is an optimized solution to localize and detect the presence of weapon objects using Neural Networks. This research focuses on both unified and II-stage object detectors whose resultant model not only detects the presence of weapons but also classifies with respective to its weapon classes, including handgun, knife, revolver, and rifle, along with person detection. This research focuses on YOLOv5 (You Look Only Once) family and Faster RCNN family for model validation and training. Pruning and Ensembling techniques were applied to YOLOv5 to enhance their speed and performance. YOLOv5 models achieve the highest score of 78% with an inference speed of 8.1ms. However, Faster R-CNN models achieve the highest AP 89%.
Uncertainty Estimation in Neural Networks Through Multi-Task Learning
Authors: James Ashish , James Anusha
Published: August 2023

The impressive predictive performance of deep learning techniques on a wide range of tasks has led to its widespread use. Estimating the confidence of these predictions is paramount for improving the safety and reliability of such systems. However, the uncertainty estimates provided by neural networks (NNs) tend to be overconfident and unreasonable. Previous studies have found out that ensemble of NNs typically produce good predictions and uncertainty estimates. Inspired by these, this paper presents a new framework that can quantitatively estimate the uncertainties by leveraging the advances in multi-task learning through slight modification to the existing training pipelines. This promising algorithm is developed with an intention of deployment in real world problems which already boast a good predictive performance by reusing those pretrained models. The idea is to capture the behavior of the trained NNs for the base task by augmenting it with the uncertainty estimates from a supplementary network. A series of experiments show that the proposed approach produces well calibrated uncertainty estimates with high quality predictions.
Answer Set Programming (DLV – Clingo):Connect 4 Solver
Authors: Cuapa C Rosalba , Zacarias F Fernando , Ponce Adair
Published: August 2023

Answer set programming is an approach that has recently gained a lot of popularity in solving complex problems due to its efficient knowledge representation and reasoning. Knowledge is represented as answer set programs, and reasoning is performed by answer set solvers. Answer set programming enables default reasoning, which is required in commonsense reasoning. In this paper, we discuss the potential role of answer set programming (ASP) in the context of approaches to the development of agents especially in the realm of Computational Logic. So, we focus on the usage of DLV for solving problems in a declarative manner particularly, in the solution of the game “connect four”. Additionally, we present the solution to this same problem from Clingo's perspective. We address this challenge with the ASP system clingo and its grounding and solving components by equipping them with well-defined generic interfaces facilitating the manifold integration efforts.
A Comparative Study for Block Chain Applications in the MANET
Authors: S Sangheethaa
Published: August 2023

MANET- Mobile Ad-hoc Networks are famous for their infrastructure-less arrangement for communication. In this network, nodes are self-organized and can act as router. They are battery operated and self-organizing. Block chain is a new concept from 2008 and researchers are trying the possible application of Block chain in many sectors including MANETs. This paper surveys the existing researches done in applying block chain in a MANET environment. Block chain is mainly used in MANETs for improving security while routing packets from one node to another. Some researchers have proposed trust models using block chain. This paper reviews some of the existing approaches where block chain is used in MANETs for routing the packets, creating trust models, and dealing with network partitioning problem and scalability problem. This paper acts as a review paper to study on block chain applications in MANET.
Real-World Multimedia Streaming for Software Defined Vehicular Ad Hoc Networks
Authors: P. Sarvade Varun , Kulkarni ShrirangAmbaji
Published: August 2023

Multimedia services with required Quality of Service (QoS) is one of the most critical challenges in Software Defined Network (SDN) based Vehicular Ad-Hoc Networks (VANETs). It forms an essential part of the Intelligent Transport System (ITS), where infotainment services play an essential role.Streaming multimedia is one of the most popular applications and has a high demand for VANET infotainment services. The major issues for multimedia streaming on VANET are scalability, mobility of vehicles, frequent connection failures, frequent change in network topology, and distributed architecture with heterogeneous devices. To overcome these problems and provide a better QoS, we propose using a hybridarchitecture with a combination of VANET and SDN called Software-Defined Vehicular Networks (SDVN). This work presents a modified POX controller-based SDN framework for VANETs, especially for multimedia streaming applications in realistic traffic patterns. The proposed work has a real-world setup developed using Simulation of Urban Mobility (SUMO), where iPerf generates multimedia traffic. Also, streaming standard-definition YouTube videos in real-time between the vehicular nodes was done. The modified POX controller could take advantage of the centralised perspective of the network for action determination, and the integrated spanning tree algorithm reduced the redundancy. Despite the dynamic nature of the testing environments, the proposed Modified POX Controller consistently outperformed VANET, with up to 21 to 42% better packet delivery ratio for higher data transfer rates. The overall improvement in QoS parameters also accompanies an improvement in the consumers Quality of Experience (QoE) factors.
Efficient ECC-Based Authentication Scheme for Fog-Based IoT Environment
Authors: Shaaban Mohamed Ali , S. Alsharkawy Almohammady , T. AbouKreisha Mohammad , Razek Mohammed Abdel
Published: August 2023

The rapid growth of cloud computing and Internet of Things (IoT) applications faces several threats, such as latency, security, network failure, and performance. These issues are solved with the development of fog computing, which brings storage and computation closer to IoT-devices. However, there are several challenges faced by security designers, engineers, and researchers to secure this environment. To ensure the confidentiality of data that passes between the connected devices, digital signature protocols have been applied to the authentication of identities and messages. However, in the traditional method, a user's private key is directly stored on IoTs, so the private key may be disclosed under various malicious attacks. Furthermore, these methods require a lot of energy, which drains the resources of IoT-devices. A signature scheme based on the elliptic curve digital signature algorithm (ECDSA) is proposed in this paper to improve the security of the private key and the time taken for key-pair generation. ECDSA security is based on the intractability of the Elliptic Curve Discrete Logarithm Problem (ECDLP), which allows one to use much smaller groups. Smaller group sizes directly translate into shorter signatures, which is a crucial feature in settings where communication bandwidth is limited, or data transfer consumes a large amount of energy. In this paper, we have chosen the safe curve types of elliptic-curve cryptography (ECC) such as M221, SECP256r1, curve 25519, Brainpool P256t1, and M-551. These types of curves are the most secure curves of other curves of ECC as their security is based on the complexity of the ECDLP of the curve. And these types of curves exceed the complexity of the ECDLP. A valid signature can be generated without reestablishing the whole private key. ECDSA ensures data security and successfully reduces intermediate attacks. The efficiency and effectiveness of ECDSA in the IoT environment are validated by experimental evaluation and comparison analysis. The results indicate that, in comparison to the two-party ECDSA and RSA, the proposed ECDSA decreases computation time by 65% and 87%, respectively. Additionally, as compared to two-party ECDSA and RSA, respectively, it reduces energy consumption by 77% and 82%.
Intrusion Detection System(IDS) Development Using Tree-Based Machine Learning Algorithms
Authors: Chimphlee Witcha , Chimphlee Siriporn
Published: August 2023

The paper proposes a two-phase classification method for detecting anomalies in network traffic, aiming to tackle the challenges of imbalance and feature selection. The study uses Information Gain to select relevant features and evaluates its performance on the CICIDS-2018 dataset with various classifiers. Results indicate that the ensemble classifier achieved the highest accuracy, precision, and recall. The proposed method addresses challenges in intrusion detection and highlights the effectiveness of ensemble classifiers in improving anomaly detection accuracy. Also, the quantity of pertinent characteristics chosen by Information Gain has a considerable impact on the F1-score and detection accuracy. Specifically, the Ensemble Learning achieved the highest accuracy of 98.36% and F1-score of 97.98% using the relevant selected features.
Machine Learning Based Ensemble Classifier for Android Malware Detection
Authors: Sumalatha P , Mahalakshmi G.S
Published: August 2023

Malware problem has infiltrated into every aspect of cyber space including Android mobiles. Due to proliferation of Android applications and widespread usage of smartphones, malware problem is causing significant damage to mobile users and application vendors. With the emergence of Artificial Intelligence (AI), machine learning (ML) models are widely used for detection of Android malware. However, many of the existing methods focused on static or dynamic data to train classifiers for malware detection. In this paper, we propose an ensemble model with intelligent methods that are empirically selected. Only the malware detection models with highest accuracy are chosen to be part of stacking ensemble model. An algorithm named Stacking Ensemble for Automatic Android Malware Detection (SE-AAMD)is proposed and implemented. We made three experiments with the same algorithm but three different datasets reflecting features obtained through different modus operandi. Each dataset is found to have influence on the performance of the models. However, in all experiments, the ensemble approach showed highest performance. The proposed method can be used in improving security for Android devices and applications.
Ransomware Attack Detection based on Pertinent System Calls Using Machine Learning Techniques
Authors: Dib Ahmed , Ghazi Sabri , Mehdi Mendjel Mohamed Said
Published: August 2023

In the last few years, the evolution of information technology has resulted in the development of several interesting and sensitive fields such as the dark Web and cyber-criminality, especially using ransomware attacks. This paper aims to bring out only critical features and make their observation, or not, in software behaviour sufficient to decide whether it is ransomware or not. Therefore, we propose a new solution for ransomware detection based on machine learning algorithms and system calls. First, we introduce our produced dataset of collected system calls of both ransomware and Benignware. Then, we push preprocessing steps deeply to reduce efficiently data dimensionality. After that, we introduce a new technique to select pertinent features. Next, we bring out the critical system calls, their importance and their contribution to the distinction between dataset elements. Finally, we present our model that achieves an overall accuracy of 99.81% after K-Fold cross-validation.
On Run-Length-Constrained Binary Sequences
Authors: M. Psillakis Zaharias
Published: August 2023

A class of binary sequences, constrained with respect to the length of zero runs, is considered. For such sequences, termed (d, k)-sequences, new combinatorial and computational results are established. Explicit expressions for enumerating (d, k)-sequences of finite length are obtained. Efficient computational procedures for calculating the capacity of a (d, k)-code are given. A simple method for constructing a near-optimal (d, k)-code is proposed. Illustrative numerical examples demonstrate further the theoretical results.
Transforming Software Requirements into Test Cases via Model Transformation
Authors: Kesserwan Nader , Al-Jaroodi Jameela , Mohamed Nader , Jawhar Imad
Published: August 2023

Executable test cases originate at the onset of testing as abstract requirements that represent system behavior. Their manual development is time-consuming, susceptible to errors, and expensive. Translating system requirements into behavioral models and then transforming them into a scripting language has the potential to automate their conversion into executable tests. Ideally, an effective testing process should start as early as possible, refine the use cases with ample details, and facilitate the creation of test cases.We propose a methodology that enables automation in converting functional requirements into executable test cases via model transformation. The proposed testing process starts with capturing system behavior in the form of visual use cases, using a domain-specific language, defining transformation rules, and ultimately transforming the use cases into executable tests.
The Use of the Muroja'ah Method in Improving of Reading Al Qur'an
Authors: Saputra Rijal , Suhono Suhono , Irhamudin Irhamudin , Wicaksono Helmi
Published: August 2023

The article aimed to determine the use of the muroja'ah method in improving the students to read the Al Qur’an at Junior High School IT Hidayatu Muslimin and Eureka English Course. This study used a qualitative method. The sample was 30 students and collecting data used observation, interviews and documentation. While the analysis technique used triangulation. The results of showed that the use of muroja'ah which was applied to class VII students of SMP IT Hidayatu Muslimin and studentas of Eureka English Course used the muroja'ah method overcome children's difficulties in reading the Qur'an. Many changes have occurred, Al-Qur'an reading activities were also more effective and have been carried out properly. In the Al-Qur'an reading activity using the muroja'ah method there are still some children who still experience difficulties in reading the Al-Qur'an but the teacher continues to guide the child until he is fluent in reading the Al-Qur'an.

Keywords: Muroja'ah Method, Improving Reading Al Qur’an, Reading Al Qur’an
Perbandingan Virgin Coconut Oil dan Curcuma Domestica Masa Kehamilan dengan Leukhore
Authors: Ulfah Maria , Oktaviani Pearly Otis Putri
Published: August 2023

It is estimated that 75% of women in Indonesia have experienced vaginal discharge once in their life. This study aims to determine the ratio of virgin coconut oil and curcuma domestica to leukhore during pregnancy. This type of research is a comparative study, namely comparing Virgin Coconut Oil with Curcuma Domestica. The population in this study were pregnant women in their first trimester. This population was in the working area of ​​the Losarang Public Health Center, Indramayu Regency, from March to May as many as 116 pregnant women in their first trimester. The sample technique used was purposive sampling, the sample in this study was 44 respondents. The results of the analysis of the Mann-Whitney Test obtained data that curcuma domestica reduced significantly with a calculated F value of 8,485 and a p-value of 0.007 <0.05. So it can be concluded that the use of curcuma domestica more significantly reduces the incidence of abnormal vaginal discharge compared to the use of virgin coconut oil.
Conference_Proceedings ISCRE -2023 -Volume 6- Special Issue 1
Authors: MARE
Published: August 2023

4th International Scientific Conference for Research & Ethics

 March 17-18, 2023 Polydisciplinary Faculty of Taroudant/ Taroudannt City, Morocco
Sosialisasi Penggunaan Media Sosial Berdasarkan Nilai – Nilai Pancasila Bagi Remaja di SMK Negeri 1 Kefamenanu
Authors: Sani Feka Yanuarius , Markus Pareto Keraf Fransiskus , Oetpah Finsensius , Nurlailah Nurlailah
Published: August 2023

Media sosial merangkap fungsi sebagai sarana penyampaian informasi yang lebih banyak digunakan dan mudah diakses oleh berbagai macam tingkat kalangan masyarakat bagi masyarakat Indonesia saat ini. Tingkat penggunaan media sosial tertinggi untuk keperluan pertemanan dan akses informasi. Hal tersebut dilihat dari pilihan masyarakat dalam penggunaan aplikasi seperti Instagram, Facebook, Twiter, Path, WhatsUpp dan lainnya. Kemajuan teknologi di waktu sekarang menjadi trend adalah berbagi foto, informasi, curahan perasaan dan lain sebagainya lewat media sosial harus menjadi kesadaran pribadi setiap pengguna dalam meperhatikan nilai dan etika.  Tujuannya dari sosialisasi ini semakin memahami ketika menggunakan media sosial menghindari Bahasa kasar, Bahasa provokatif, Sara atau Pornografi, status atau artikel yang dianggap hoax. Kesadaran membangun kebiasaan dalam berinterkasi di media sosial menggunakan etika berasaskan nilai – nilai Pancasila. Tim pengabdian melaksanakan sosialisasi di SMK Negeri 1 Kefamenau dengan meberikan teori dan simulasi atau praktek penggunaan bermedia sosial berlandaskan nilai – nilai Pancasila. Metode yang digunakan ceramah, diskusi tanya jawab, dan simulasi/praktik. Siswa – siswi dan guru SMK Negeri 1 Kefananu menyampaikan terima kasih atas kesempatan dari Tim pengabdian, karena sosialisasi ini memberikan pengetahuan, kemampuan dan kesadaran dalam menggunakan media sosial dengan beretika sesuai nilai – nilai Pancasila.
Peningkatan Pengetahuan Siswa Tentang Tanggap Bencana di SMK Swasta Imelda Medan
Authors: Linda Rambe Nova , BR. Sebayang Wellina , Br S. Kembaren Martalena , Warnelis Sinaga Elvalini , Lestari Simamora Debora , Syahputra Bukit Dhani , Susanti Pasaribu Riska , Natalia Br Sinuhaji Lidya , Masyitah Panjaitan Arifa , Aini Fadilah , Nisa Khairun , Sudaryati Etti
Published: August 2023

Indonesia secara geografis terletak dirangkaian lempeng tektonik, sehingga menjadikan Indonesia menjadi negara yang rawan akan bencana alam. 75% sekolah di indonesia berada pada daerah atau lokasi yang rawan akan bencana alam, bahkan disetiap tahunnya faktor fisik lingkungan sekolah mengalami kerusakan diakibatkan oleh bencana alam, tentu saja bencana tersebut dapat menghambat proses pendidikan anak di sekolah. Komunitas sekolah mempunyai peran penting yang sangat besar sebagai sumber pengetahuan untuk anak. Fokus permasalahan pada pengabdian ini adalah mengacu pada penanggulangan bencana di sekolah dengan memenuhi acuan seperti fasilitas, manajemen bencana, serta pemberian pendidikan pencengahan risiko bencana yang ada pada SMK Swasta Imelda Medan. Responden penyuluhan berjumlah 35 siswa di SMK Swasta Imelda Medan. Teknik pengambilan sampel menggunakan metode kuantitatif dengan simple random sampling. Tujuan dari pengabdian adalah untuk meningkatkan pengetahuan siswa akan kesedian peralatan dan perlengkapan serta pendidikan dalam penanganan bencana disekolah di SMK Swasta Imelda Medan.
Hasil pengabdian masyarakat menunjukkan bahwa penanganan penanggualangan pencegahan akan bencana di sekolah si SMK Swasta Imelda Medan dari segi fasilitas sudah ada namun belum lengkap, manajeman bencana disekolah masih belum terdapat tim petugas siap siaga bencana, dan pendidikan pengetahuan kepada siswa dalam pencengahan dan pengurangan risiko bencana disekolah masih belum terintegrasi sesuai dengan kurikulum. Setelah diberikan penyuluhan diperoleh bahwa terjadi peningkatan pengetahuan partisipan tentang penanggulangan bencana di Sekolah yang semula nilai rata-rata 40,32 menjadi 71,68. Kesimpulan sarana parasarana siaga bencana masih perlu dilengkapi dan dipelihara secara rutin, untuk hal tersebut pihak-pihak komite sekolah dan warga sekolah serta bagain-bagian yang terlibat menjadi tolak ukur acuan akan terpenuhinya sarana dan prasarana dalam penenggulangan bencana disekolah.
Wujudkan Kampung Sehat dan Tangguh Pada Masa Pandemi Covid-19 Melalui Strategi Pemberdayaan dan Kemitraan Interdisiplin Ilmu di Surokarsan, Wirogunan, Yogyakarta
Authors: Rianita Elfrida Sinaga Mei , Ikaningtyas Nurlia , Pujiastuti Diah , Adik Putra Bambang Kurniawan Erik , Riendrasiwi Noviyanti
Published: August 2023

Dampak Covid-19 bagi individu dan masyarakat sangat mempengaruhi status kesehatan tidak hanya secara fisik, tetapi juga psikologis, sosial termasuk di Kampung Surokarsan. Kampung surokarsan memiliki permasalahan kompleks dari usia sekolah sampai lansia. Mewujudkan masyarakat sehat dan tangguh diperlukan peran dari berbagai pihak melalui strategi pemberdayaan dan kemitraan untuk meningkatkan kesehatan dan sebagai sarana yang memungkinkan orang-orang yang kurang berdaya untuk mendapatkan kontrol atas kehidupannya dan mandiri. Adapun tujuan pengabdian masyarakat ini adalah untuk mewujudkan kampung sehat dan tangguh pada masa pandemi. Metode pengabdian dilakukan dengan strategi pemberdayan dan kemitraan dengan tahapan focus group discussion, skrining kesehatan jiwa, skrining kognitif, mental dan kemampuan fisik lansia, edukasi untuk peningkatan literasi, dan evaluasi. Didapatkan hasil bahwa kegiatan yang dilakukan terjadi peningkatan pengetahuan 80%, peningkatan literasi membaca 67%, terbentuk 21 kader kesehatan, dari 44 orang usia dewasa terdapat 37 depresi normal, 6 orang depresi ringan, 1 orang depresi sedang, cemas normal 32, cemas ringan 6 orang, cemas sedang 6 orang, sedangkan stres normal 44 orang, dari 44 lansia 33 lansia normal, kemungkinan depresi 11 orang, lansia yang mengalami gangguan ingatan normal 40 orang, gangguan ingatan sedang 4 orang, lansia dengan tingkat ketergantungan aktivitas fisik ringan 44 orang. Upaya pemberdayaan dan kemitraan yang dilakukan dapat terealisasi melalui kader kesehatan yang terbentuk. Pemberdayaan kader dapat menimbulkan kemauan yaitu kecenderungan untuk melakukan suatu tindakan atau sikap untuk meningkatkan kesehatan masyarakat dalam suatu masyarakat sehingga masyarakat dan kampung sehat dan tangguh dapat terwujud.
Sosialisasi Etika Berlalu Lintas Pada Anak Di Medan Marelan
Authors: Amir Saiful , Lestari Wiwik , Ridho Faizin
Published: August 2023

Masalah utama dalam berlalu lintas adalah tingginya angka kecelakaan yang terjadi selama akhir-akhir ini, yang dapat menimbulkan kerugian bagi sesama pengguna jalan. Di Sumatera Utara tahun 2019 terdapat 6.580 kasus kecelakaan angka ini lebih besar daripada tahun 2018 tercatat 5.990 kasus dan ini dapat diperdiksi meningkat di tahun akan datang. Hal ini diakibatkan pelanggaran lalu lintas yang cendrung ketidak pedulian terhadap keselamatan. Banyak faktor pelanggaran lalu lintas terjadi mulai dari sarana prasarana jalan hingga pemahaman terhadap pengguna jalan. Perlu upaya bersama baik pemerintah atau institusi pendidikan untuk melakakukan sosialisasi dan edukasi bagi masyarakat, khususnya pada anak-anak. Anak-anak perlu diajarkan mengenai pentingnya keselamatan di jalan. Pola pikir mengenai etika berlalu lintas ini dapat ditanamkan sebagai karakter positif pada anak. Tujuan kegiatan adalah meningkatkan pemahaman dan kesadaran terkait etika pengguna jalan serta mengembangkan dan memelihara sikap selamat dalam berlalu lintas. Pelaksanaan kegiatan dilaksanakan dengan menggunakan metode interaktif melalui cerita-cerita yang dibantu dengan alat peraga tentang rambu-rambu lalu lintas. Untuk meningkatkan respon pemahaman dan pengetahuan anak juga dibarengi dengan permainan edukatif tentang lalu lintas. Hasil yang dicapai dalam kegiatan ini adalah meningkatnya pemahaman dan pengetahuan berlalu lintas yang baik dan benar serta diharapkan dapat membangun karakter peduli dan empati terhadap sesama pengguna jalan..
Pemberdayaan Kelompok Wanita Tani Melalui Pelatihan Produksi Kopi Rendah Kafein Berbahan Biji Buah Salak
Authors: Ridwan Muhamad , Subagio Hani , Yuliawati Yuliawati , Alvin Mubarok Alvian , Setyani Atik
Published: August 2023

Perkebunan buah salak di Kabupaten Sleman, Daerah Istimewa Yogyakarta merupakan salah satu tumpuan utama perekonomian masyarakat di lereng Gunung Merapi. Namun fakta di lapangan menunjukkan beberapa permasalahan seperti fluktuasi harga buah salak dan karakteristik buahnya yang mudah membusuk, ancaman erupsi Gunung Merapi, serta kurangnya inovasi warga setempat dalam mengoptimalkan potensi buah salak. Oleh karena itu, diperlukan solusi melalui optimalisasi potensi buah salak guna mengurangi dampak permasalahan tersebut melalui inovasi pengolahan biji buah salak menjadi produk dengan wujud seperti kopi dengan teknik yang tepat untuk menghasilkan karakteristik produk yang sesuai kebutuhan pasar. Program pemberdayaan ini dilaksanakan dalam beberapa tahapan diantaranya yaitu koordinasi dengan ketua kelompok wanita tani, sosialisasi program kepada peserta, persiapan pelatihan, pelaksanaan pelatihan dan pendampingan, serta evaluasi dan tindak lanjut. Hasil dari program pemberdayaan ini yaitu seluruh peserta pelatihan telah terampil dalam mengelola bahan baku biji buah salak dan memproduksinya menjadi kopi biji salak. Diperlukan adanya program lanjutan untuk mencapai tujuan besarnya yaitu mencakup asas kebermanfaatan bagi para petani dan buruh tani salak sebagai upaya meningkatkan kesejahteraan ekonomi, bagi konsumen yang membutuhkan variasi minuman kopi yang rendah kafein, serta bagi pemerintah dalam rangka mendukung ikon daerah yang mendukung sektor pariwisata dan ekonomi kreatif.
Pelatihan Membuat Media Pembelajaran Berbantuan Geogebra Untuk Mengembangkan Kreativitas Guru TK YP Tridaya Mandiri
Authors: Rusmini Rusmini , Sari Harahap Fitrah , Wahyu Pratama Muhammad , Haidil Umam M.
Published: August 2023

Kreativitas adalah kemampuan untuk mempergunakan imajenasi dari berbagai kemungkinan yang diperoleh dari interaksi dan ide atau gagasan orang lain untuk membuat koneksi dan  mendapatkan hasil baru dan bermakna. Kreativitas sangat penting, guru tanpa kreativitas pembelajaran di kelas akan terlihat monoton dan kurang bermakna. Oleh karena itu guru perlu mengembangkan daya kreativitas pada saat membuat media pembelajaran. Pelatihan membuat media pembelajaran berbantuan GeoGebra guru TK YP Tridaya Mandiri bertujuan memberikan motivasi dan arahan membuat media pembelajaran. Diberikan tutorial praktek langsung membuat animasi gerak berupa aktivitas yang menarik bagi anak usia dini. Dengan ketertarikan anak menjadi daya ingat dan sebagai informasi baru yang berguna untuk mengetahui seberapa jauh logika matematis anak terhadap gambar-gambar yang ada hubungannya dengan bentuk bentuk geometri. Setelah diberikan pelatihan selama satu hari dalam bentuk workshop kepada guru TK YP Tridaya Mandiri dan dilakukan evaluasi dengan tugas membuat animasi sesuai ide peserta pelatihan maka diperoleh hasil kreativitas guru sangat signfikan. Berdasarkan hasil angket yang dibagi kepada peserta pelatihan dan observasi pada saat proses pelatihan diperoleh gambaran tentang  motivasi dan antusias peserta pelatihan sangat baik.
LITERATURE REVIEW : ANALISIS IMPLEMENTASI KEBIJAKAN PENURUNAN STUNTING DI WILAYAH PESISIR MEDAN BELAWAN
Authors: Susilawati Susilawati , HENDRA NADIA HENDRA PRATAMA
Published: August 2023

Balita Pendek (Stunting) adalah status gizi yang didasarkan pada indeks PB/U atau TB/U dimana dalam standar antropometri penilaian status gizi anak, hasil pengukuran tersebut berada pada ambang batas (Z-Score) <-2 SD sampai dengan -3 SD (pendek/ stunted) dan <-3 SD (sangat pendek / severely stunted). Stunting adalah masalah kurang gizi kronis yang disebabkan oleh asupan gizi yang kurang dalam waktu cukup lama akibat pemberian makanan yang tidak sesuai dengan kebutuhan gizi. Stunting dapat terjadi mulai janin masih dalam kandungan dan baru nampak saat anak berusia dua tahun (Kementerian Kesehatan Republik Indonesia, 2016). Metode yang digunakan adalah menggunakan studi literatur dari berbagai jurnal internasional maupun nasional, metode ini berupaya untuk meringkas kondisi pemahaman terkini tentang suatu topik. Berdasarakan hasil wawancara dengan para informan diperoleh keterangan bahwa standar dalam menjalankan kebijakan percepatan penurunan stunting, pemerintah sudah memiliki standar yakni dengan adanya Peraturan Medan Belawan Tahun 2020 Tentang Percepatan Penurunan Stunting yang sesuai dengan amanat Peraturan Presiden RI No. 42 tahun 2013 tentang Gerakan Nasional Percepatan Perbaikan Gizi yang sekarang digantikan menjadi Peraturan Presiden Republik Indonesia Nomor 72 Tahun 2021 Tentang Percepatan Penurunan Stunting.