bluuebunny/crossref_metadata_2025 huggingface dataset:
Pemanfaatan Media Pembelajaran Kahoot dalam Mata Pelajaran Sejarah di SMAN 68 Jakarta
Authors: Syah Randi , Siburian Junia , Pratama Ardin Yuli , Safani Muhammad
Published: October 2023

Penelitian ini bertujuan untuk menginvestigasi pemanfaatan media pembelajaran Kahoot dalam mata pelajaran Sejarah di SMA N 68 Jakarta. Penelitian ini dilakukan dengan menggunakan metode kualitatif deskriptif dan melibatkan guru Sejarah serta siswa sebagai partisipan. Data penelitian dikumpulkan melalui observasi kelas, wawancara dengan guru, dan analisis dokumen terkait. Hasil penelitian menunjukkan bahwa pemanfaatan Kahoot dalam pembelajaran Sejarah memberikan manfaat yang signifikan. Penggunaan Kahoot meningkatkan keterlibatan dan motivasi siswa dalam pembelajaran, sambil mendorong interaksi sosial dan kolaborasi antara siswa. Guru juga melaporkan bahwa Kahoot membantu mereka dalam menyampaikan materi pembelajaran dengan cara yang menarik dan interaktif. Namun, ada beberapa tantangan yang dihadapi, termasuk keterbatasan akses teknologi. Dengan demikian, penelitian ini merekomendasikan pengembangan dan perluasan penggunaan Kahoot sebagai media pembelajaran yang efektif dalam mata pelajaran Sejarah di SMA N 68 Jakarta.Kata Kunci : media pembelajaran, Kahoot, Sejarah, SMA AbstractThis research aims to investigate the utilization of Kahoot as a learning media in the History subject at SMA N 68 Jakarta. The study adopts a qualitative descriptive approach and involves History teachers and students as participants. Data were collected through classroom observations, teacher interviews, and document analysis. The findings indicate that the use of Kahoot in History learning provides significant benefits. It enhances student engagement and motivation, while fostering social interaction and collaboration among students. Teachers also reported that Kahoot helps them deliver the learning materials in an interesting and interactive manner. However, there are challenges, including limited technological access. Therefore, this research recommends the development and expansion of Kahoot as an effective learning media in the History subject at SMA N 68 Jakarta.Keywords: learning media, Kahoot, History, high school
Pergerakan PNI Baru Menentang Ordonansi Sekolah Liar Tahun 1932-1933
Authors: Utomo Ilham Nur , Putri Sulistya
Published: October 2023

Tujuan penelitian ini adalah untuk mengetahui pergerakan PNI Baru dalam menentang Ordonansi Sekolah Liar yang dikeluarkan oleh pemerintah kolonial pada tahun 1932. Metode yang digunakan dalam penelitian ini adalah metode sejarah, yang mencakup empat tahapan, yaitu heuristik, kritik sumber, interpretasi, dan historiografi. Ordonansi Sekolah Liar secara resmi diberlakukan pada 1 Oktober 1932, yang memberi kewenangan kepada pemerintah kolonial untuk mengawasi dan mengeluarkan keputusan terhadap sekolah-sekolah partikelir yang dianggap memberikan pengajaran tidak representatif dan menyemai benih-sbenih nasionalisme. PNI Baru dalam menentang Ordonansi Sekolah Liar berfokus pada tiga cara, yaitu melalui tulisan-tulisan yang diterbitkan dalam majalah internal PNI Baru, menggelar rapat umum, dan melakukan aksi protes secara terbuka bersama dengan organisasi nasionalis lainnya. Selain itu, PNI Baru memberikan dukungan terhadap pergerakan Ki Hajar Dewantara yang dikenal sebagai pendiri Taman Siswa dan tokoh penting dalam gerakan menentang Ordonansi Sekolah Liar. Aksi-aksi penentangan yang terus disuarakan pada akhirnya berhasil mendorong pemerintah kolonial  mencabut pemberlakuan Ordonansi Sekolah Liar pada 13 Februari 1933. Kata Kunci : PNI Baru; Ordonansi Sekolah Liar; Pergerakan Nasional Indonesia. AbstractThis research aimed to find out the movement of PNI Baru in opposing the Wild School Ordinance issued by the colonial government in 1932. The method used in this research was the historical method. It consists of heuristics, source criticism, interpretation, and historiography stages. The Wild School Ordinance was officially enacted on October 1, 1932. It gave the colonial government the authority to monitor and issue decisions on private schools deemed to provide unrepresentative teaching and sow the seeds of nationalism. PNI Baru in opposing the Wild School Ordinance focused on three ways; through writings published in the PNI Baru internal magazine, holding public meetings, and conducting open protests together with other nationalist organizations. Besides, the PNI Baru gave support to the movement of Ki Hajar Dewantara, who is known as the founder of Taman Siswa and an important figure in the movement against the Wild School Ordinance. Opposition actions that continued to be conducted in the end succeeded in encouraging the colonial government to revoke the implementation of the Wild School Ordinance on February 13, 1933. Keywords : PNI Baru; Wild School Ordinance; Indonesian National Movement..
YENİDEN DEĞERLEME UYGULAMALARINDA SON YASAL DÜZENLEMELER VE ÖNCEKİ REVİZYONLARIN ETKİLERİ
Authors: YAVUZASLAN SÖYLEMEZ Seda
Published: October 2023

Ülkemizde yeniden değerleme uygulaması ilk kez 1984 yılında uygulanmış ve 2003 yılına kadar farklı düzenlemelerle uygulanmaya devam edilmiştir. 2003 yılında enflasyon düzeltme şartlarının oluşması ile 2004 yılında ilk kez enflasyon düzeltmesi uygulanmış ve yeniden değerleme uygulamadan kaldırılmıştır. 2005 yılında enflasyon şartları oluşmadığı için ne enflasyon düzeltmesi ne de yeniden değerleme uygulaması altın işi ile uğraşan işletmeler dışındaki işletmelerde uygulanmamıştır. Daha sonra VUK Geçici 31. Madde kapsamında 2018 yılında ve 2021 yılında tüm işletmelere tekrar yeniden değerleme olanağı tanınmış ancak devlete vergi verme zorunluluğu da getirilmiştir. Ocak 2022’de de VUK’a eklenen geçici 33. Madde ile ; 2021 ve 2022 yılı üç geçici ve hesap dönemi ile 2023 yılı üç geçici vergi dönemlerinde, enflasyon düzeltmesi şartlarının oluşup oluşmadığına bakılmaksızın enflasyon düzeltmesi yapılmayacağı ve bu sayılan dönemlerde yeniden değerleme uygulamasının yapılabileceği belirtilmiştir. Bu yasal düzenleme ile yeniden değerleme yapmak isteyen uygulayıcılara iki uygulama seçeneği sunulmuştur. 1.seçenek ; önce tek seferlik yeniden değerleme uygulaması yapmak; sonra sürekli yeniden değerlemeyi uygulamak (daha avantajlı olabilmektedir); 2.seçenek; sadece sürekli yeniden değerleme uygulamak.

Çalışmada geçmişten günümüze yeniden değerleme uygulamaları ve en son yayınlanan VUK mükerrer 298 inci maddenin (Ç) fıkrası ile geçici 32 nci madde kapsamındaki sürekli ve tek seferlik yeniden uygulamalarının birbirleri ile ilişkileri, farklılıkları ve önceki uygulamaların yeni uygulamalar üzerindeki etkileri ortaya konmaya ve dikkat çeken noktaların altı çizilmeye çalışılmıştır. Uygulama örneğinde işletmenin sadece sürekli yeniden değerleme uyguladığında ortaya çıkan net değer artışı ile önce tek seferlik yeniden değerleme sonra sürekli yeniden değerleme uyguladığında ortaya çıkan net değer artışı arasındaki anlamlı fark gösterilmiştir.
İşletmelerde Sürdürülebilir Yönetim Muhasebesinin Gerekliliği
Authors: ÖZYİĞİT Hüseyin
Published: October 2023

Günümüz iş dünyasında işletmelerin, daha çevresel ve sosyal açıdan faaliyetlerini gerçekleştirme konusunda baskı altında olması, sürdürülebilir yönetim muhasebesini önemli hale getirmektedir. Bu çalışmanın amacı, sürdürülebilir yönetim muhasebesinin; içeriği, önemi ve özellikleri hakkında bilgi vererek işletmeler açısından gerekliliğini özlü bir şekilde ortaya koymaktır. Çalışmada, nitel araştırma yöntemlerinden tematik analiz tekniği kullanılmıştır. Tematik analiz, veriler içindeki kalıpları, anlamları ve ilişkileri belirlemeye ve keşfetmeye olanak tanımaktadır. Çalışma verilerinin analizinde birbirini takip eden altı analiz aşaması kullanılmıştır. Sürdürülebilir yönetim muhasebesi araçları ve uygulamaları, sürdürülebilir yönetim muhasebesinin değerlendirilmesi ve sürdürülebilir yönetim muhasebesinin uygulama zorlukları ve gelecekteki gelişimi olmak üzere üç tane ana tema belirlenmiş ve bu temalara yönelik bulgular açıklanmıştır. Sonuç olarak, sürdürülebilir yönetim muhasebesinin; işletmelerin çevresel ve sosyal performanslarını iyileştirerek, maliyetlerini düşürerek ve paydaşlar nezdindeki itibarlarını artırarak uzun vadeli sürdürülebilirlik ve kârlılık elde etmelerine yardımcı olacağı düşünülmektedir.
Pelatihan Pembuatan Media Pembelajaran Berbasis Canva Untuk Guru MANW Unwanul Falah Paok Lombok
Authors: Zubair Muh. , Sawaludin Sawaludin , Alqadri Bagdawansyah , Kurniawansyah Edy
Published: October 2023

Pemanfaatan teknologi dalam mengembangkan dan pengimplementasian materi diperlukan keterampilan membuat disain media yang menarik dan menyenangkan. Canva merupakan salah satu tools desain grafis yang dirancang untuk memudahkan penggunanya  membuat berbagai desain kreatif dan inovatif secara online. Pada kegiatan pengabdian kepada masyarakat ini, dilaksanakan pelatihan pembuatan media pembelajaran berbasis canva bagi guru MA NW Unwanul Falah Paok Lombok. Pemilihan aplikasi canva yang akan digunakan karena penggunaannya tidak sulit dan terdapat versi yang tidak berbayar. Selain itu, canva juga menyediakan berbagai template yang menarik sehingga guru-guru dapat bebas memilih template yang sesuai dengan kebutuhan. Kegiatan ini bertujuan untuk meningkatkan kemampuan peserta pelatihan dalam menggunakan canva untuk membuat media pembelajaran yang menarik dan menyenangkan. Metode pelakasanaan kegiatan Pengabdian Kepada Masyarakat ini menggunakan metode pelatihan. Kegiatan pelatihan dilaksanakan dengan menggunakan pola workshop seperti : ceramah, praktik dan diskusi/tanyajawab. Kegiatan dilaksanakan melalui tiga tahap yaitu : (1) persiapan, (2) pelaksanaan pelatihan dan (3) evaluasi kegiatan.  Penyampaian materi  dilanjutkan  dengan  praktik  pembuatan  media pembelajaran interaktif.  Kegiatan  ini  diikuti  oleh  43  guru-guru  MA NW Unwanul Falah Paok Lombok. Pelatihan Pembuatan Media Pembelajaran berbasis canva terselenggara dengan baik serta mampu meningkatkan kemampuan guru MA NW Unwanul Falah Paok Lombok dalam membuat media pembelajaran yang menarik dan interaktif. Peserta memiliki respon yang baik dan merasa antusias selama pelatihan berlangsung. Setelah selessainya kegiatan pelatihan, semua guru atau peserta mampu mengoprasikan aplikasi canva untuk membuat  media pembelajaran iteraktif. Berdasarkan hasil respon, semua peserta mengatakan sangat setuju dengan penggunaan aplikasi canva dalam menyiapkan pembelajaran yang menyenangkan buat siswa.
Implementation of Science Education for Junior High School Students in Lampung Province During the Covid-19 Pandemic
Authors: Hendrowati Tri Yuni , Nurmitasari N , Muhammad Badrun
Published: October 2023

Science education is one of the important subjects in the scientific structure studied in our world of education. During the Covid-19 pandemic by considering the condition of the readiness of supporting infrastructure for online learning implementation, IT-based teacher skills, and online learning evaluation, this science subject was transformed to students. The purpose of this study is to describe the planning, organizing, implementing, and monitoring of Science Education, especially in public junior high schools in Lampung Province. This research is a qualitative research with an educational ethnography study design, and the research participants are principals of MKKS junior high schools in Lampung Province. This study used interviews, observations and documentation to collect data, which were then evaluated using the interactive model analysis. The findings of this study are as follows: (1) Natural Science lesson plans are prepared by taking into account student characteristics, materials, and the use of applications for learning implementation; (2) the organization of Natural Science learning begins with the formation of Whatsapp groups, the direction of learning meetings using Google Classroom and Google Meet by sharing links through Whatsapp groups; and (3) optimization of learning implementation in this science subject is still limited: 50% of public junior high schools in Lampung Province have limited internet bandwidth; (4) monitoring, science subject teachers have difficulty in conducting learning assessment because they cannot organize students in a perfect setting.
Development of Flipbook-Based Teaching Materials for Learning in Elementary School’s
Authors: Putra Alpidsyah , Sidiq Fadhil , Mahlianurrahman Mahlianurrahman
Published: October 2023

Abstract: The use of digital teaching materials in the 21st century is considered very relevant to the development of information and communication technology in learning in elementary schools. Good teaching materials are teaching materials that include all the material needed in learning activities. This research aims to develop flipbook-based teaching materials in project activities to strengthen the profile of Pancasila students (P5) in elementary schools. The methodology used in this research uses the ADDIE model (analysis, design, development, implementation, and evaluation). Data analysis techniques use qualitative data analysis and quantitative data analysis. This research was conducted at SD Negeri 1 Langsa City, SD Negeri 11 Langsa City and SD Negeri 2 Seulalah. Based on the research results, the percentage of material expert validation was 88.95% with a very valid category; media expert validation obtained a percentage of 90.57% in the very valid category, while learning design experts obtained a percentage of 86.25% in the very valid category. From the research results above, it shows that this flipbook teaching material is very suitable to be applied as digitalization-based teaching material in the project to strengthen the profile of Pancasila students in elementary schools.
Strongly (E,F)-convexity with applications to optimization problems
Authors: Enad Ammar A. , Majeed Saba N.
Published: October 2023

In this paper, a new class of nonconvex sets and functions called strongly -convex sets and strongly -convex functions are introduced. This class is considered as a natural extension of strongly -convex sets and functions introduced in the literature. Some basic and differentiability properties related to strongly -convex functions are discussed. As an application to optimization problems, some optimality properties of constrained optimization problems are proved. In these optimization problems, either the objective function or the inequality constraints functions are strongly -convex.
Influence of Heat Transfer on Magnetohydrodynamics Oscillatory Flow for Carreau-Yasuda Fluid Through a Porous Medium
Authors: Migtaa Hazim Aneed , Salih Al- Khafajy Dheia G.
Published: October 2023

This paper, we have examined the influence of  transfer the heat on the magnetohydrodynamics (MHD) oscillatory flow of Carreau-Yasuda fluid through porous medium for two types of geometries "Poiseuille flow and Couette flow". We have solved the problem by using the perturbation technique in terms of the Weissenberg number (We), discussed and analyzed the numerical and arithmetical results of the effect of several parameters, namely The number of Darcy, the number of Reynold, the number of Peclet, the parameter of magnetic, the number of Grashof, the number of Weissenberg, frequency of the oscillation and radiation parameter  for the velocity and temperature that are effective on the fluid movement by using MATHEMATICA program using illustrations.
Studying The Effect of Sampling Time and Network Load on Wireless Networked Control Systems.
Authors: Abdul-Hussain Russul N. , Awad Osama A.
Published: October 2023

Wireless networked control systems (WNCS) are considered one of the main attracting topics in the control, communication and computing domains. One of the main problems that face these systems is the various time delays which occur in the measurements. The control design process would be complicated if there is a time delay in the feedback loop.  Moreover, this delay affects the system performance in terms of instability. The literature of WNCS shows that the available controllers can deal with a limited number of nodes. Beyond this limit, the system becomes unstable. In this paper, an optimized Particle Swarm Optimization (PSO)-based PID and FOPID controllers are proposed for WNCS to control the plant wirelessly. The proposed controllers aim at minimizing the time delays and can make the system remains stable when the network tackles a large number of nodes with variable length packet sizes. The performances of the proposed optimized controllers are compared to show which one of them can be more robust against the challenges of WNCS, namely varying time-delays, to handle a greater number of nodes. The results show that the FOPID is more powerful than the PID controller.
Convolution Neural Network with Dual Tree Complex Wavelet Transform Preprocessor for Universal Image Steganalysis
Authors: Mahmoud Halah Hasan , Ahmed Hanaa Mohsin
Published: October 2023

Recently, deep learning models based on convolutional neural networks (CNN) have been used in image steganalysis problems. In this paper, we present different architecture of CNN with dual tree complex wavelet transform for preprocessing before input images put into system. The main task of this transform is for exploiting the difference between cover and stego images through shift variance property. The net consists of five successive convolutions layers. Each one following by normalization and pooling layers ends with fully connected layer. The performance of system is evaluated through accuracy, precision, recall and f-score measures. The results show effectiveness of it with more than 0.9 precision values. HUGO, WOW and UNIWARD algorithms selected for implementation.
Using space-filling curves to improve the quad tree for spatial indexing
Authors: Azeez Ali Abid Hussan , Hassan Rehab Flaih
Published: October 2023

Spatial indexes, like the ones that are based on Quad Tree, are important in spatial data-bases for the effective implementation of queries with spatial constraints, particularly in the case where queries include spatial links. The quad trees are a very interesting subject, given the fact that they give the ability to solve problems in a way that focuses only on the important areas with the highest density of information. But it is not without the disadvantages because the search process in the quartile suffers from the problem of repetition when reaching the terminal node and return to the behaviour of another way in the search and lead to the absorption of large amounts of time and storage. A database management system can handle data very easily if the object is one-dimension (sequential).

In this paper, improve the quad tree by combining one of the space filling curve types, including the Hilbert curve and the Z-ordering curve with a quad tree. It will convert from two-dimensional to one-dimensional and sequentially search and end the problem of repetition whenever it reaches a terminal node Ordinary quad tree. Resulting in reduced storage space requirements and improved implementation time.
Hybrid between Genetic Algorithm and Artificial Bee Colony for Key Generation Purpose
Authors: Taher Ali AbdulKadhim , Kadhimb Suhad Malalla
Published: October 2023

Cryptography is a significant tool for guarantee a protected and secured data. In asymmetric key algorithms, the key generation plays an important role for applied the security. This research focus on enhance genetic algorithm's population by using artificial bee colony to generate keys that are unique and random. The five statistical tests ( Frequency test (monobit test), Serial test (two-bit test), Poker test, runs test and autocorrelation test) are used to compute the fitness. The programming language Pythom3 was used in programming the proposed method. The proposed algorithm is acquired higher quality solutions within a reasonable computational time compared to traditional genetic algorithm.
Automated Analysis of Comments on Press Articles in Websites (Journalist of Articles on Al-Ahram newspaper as study case)
Authors: Arif Afra , Rahma Abdul Monem S.
Published: October 2023

Due to the increasing writers of press articles on electronic publishing sites for printed and certified newspapers, the reader faced the problem of reaching his goal by accessing these sites, which led to the neglect of a large section of important publications of press articles for the writers. The provision of an automated measure to verify the positive and negative press articles of the writers based on the analysis of readers' comments on the press articles is a necessity to see the important writers of the press articles that is compatible with corpus generated by us for inference. the proposed system was applied on ten press articles by the writer "". thses ten articles also evaluated by the experts. The project achieved the previous target and achieved a success rate. The proposed system is evaluated based on four metrics (Precision, Recall, F-measure and Accuracy) . The effectiveness results obtain by this system was (Precision= 95%, Recall= 95%, F-measure=95% and Accuracy=94%).
On DG- Topological operators Associated with Digraphs
Authors: Khaiarallha Al’Dzhabri Khalid Shea , Hamza Abedal-Hamza Mahdi , Eissa Yousif Saheb
Published: October 2023

In this paper ,we introduced new concepts of DG- topological operators such as DG- closuer ,DG- kernel ,DG- cor, and DG-intiorer and we investigated certain types between the digraphs and the topology by associated new topology on a digraph named DG- topological space .
Infected Intermediate Predator and Harvest in Food Chain
Authors: Arif Ghassan Ezzulddin , Wuhaib Sufyan Abaas , Rashad Marwa Fareed
Published: October 2023

In this paper, a mathematical model consisting of the food chain model with disease in intermediate predator is proposed and discussed. The food chain model consists of four types: prey, intermediate predator, infected intermediate predator, and top predator. We studied the solutions for the original model and positive and bounded solutions in the sub models. Also found equilibrium points with sufficient and necessary conditions. By using Jacobian matrix and Lyapunov function to provide local and global stability. Can use the harvesting to control the disease and it can be used as tool to prevent disease transformation into an epidemic. Finally, some results were illustrated in numerical simulations.
Some Properties of Algebra Fuzzy Metric Space
Authors: Kider Jehad Rmadhan
Published: October 2023

Our goal in the present paper is to introduce new type of fuzzy metric space called algebra fuzzy metric space after that some examples is introduced to illustrate this notion. Then basic properties of algebra fuzzy metric space is proved.
Weak Pseudo Quasi-2- Absorbing Submodules And Related concepts
Authors: Mohammadali Haibat Karim , Radeef Sada Emad
Published: October 2023

In this paper R stand for commutative ring with identity ,and E is a unitary left R-module. The concept of weakly quasi-2-Absorbing submodule has been generalized in this research to a Wpq-2-Absorbing submodules ,where a paper submodule H of an R-module E is a Wpq-2-Absorbiming if 0≠abcyϵH ,for a,b,cϵR, yϵE , implies that either abyϵH+Soc(E) or acyϵH+Soc(E) or bcyϵH+Soc(E) .Several characterizations ,examples and basic properties of this concept are introduced .Moreover characterizations of Wpq-2-Absorbing submodules in some types of modules are given .Keywords: Weakly quasi-2-Absorbing submodules, Wpq-2-Absorbing submodules, socel of modules ,multiplication modules ,Z-regular modules ,non-singular modules.
Optimized Deep Learning with Binary PSO for Intrusion Detection on CSE-CIC-IDS2018 Dataset
Authors: Farhan Rawaa Ismael , Maolood Abeer Tariq , Hassan Nidaa Flaih
Published: October 2023

Anomaly detection is a term refer to any abnormal behaviors, comprise security breaches of network. Deep Learning (DL)has proven its outperformance compared to machine learning algorithms in solving the complex   problems of   real-world like intrusion detection. Though, this approach need more computational resources and consumes long time. Feature selection is play significant role of choosing the best features that describes the target concept optimally during a classification process. However, when handle large number of features the selecting of such relevant features becomes a difficult task. Thus, this paper proposes using Binary Particle Swarm Optimization (BPSO) to solve the feature selection problem. Then, features selected from BPSO are evaluated on Deep Neural Networks (DNN) classifiers and the CSE-CIC-IDS2018 dataset. The result of the proposed model has shown comparable performance based on processing time, detection rate and false alarm rate comparing with other benchmark classifiers. Experimental results have shown a high accuracy of 95%.
Linear Programming Method Application in a Solar Cell
Authors: Mitlif Rasha Jalal , RASHEED Mohammed , SHIHAB Suha , RASHID Taha , Abed Hamed Saad Hussein
Published: October 2023

A new ranking function of linear programming problems to find the optimal solution of the solar cell by simplex method has been introduced in this paper. Numerical examples are given to illustrate the proposed method. The results obtained indicated that this technique is active for the PV determinations.
Deep Learning In Wireless Sensor Network
Authors: Jarah Nada B.
Published: October 2023

In the era of the development of the Internet of Things, how collecting data from sensors located everywhere in society is an important issue, and in wireless sensor networks, distributed processing technology for deep learning using advanced computing and coordination between peripherals has attracted attention. In this study, a new architecture is proposed for the distributed implementation of deep learning in a wireless sensor network where the distributed application divides the middle layer of deep learning into each sensor with the purpose of reducing traffic and reducing the load, in order to improve data processing speed, but this is done by increasing the number of connections and energy consumption, and in order to evaluate the effectiveness of the proposed method, been compared the amount of data communication and accuracy of learning between learning by using Convolutional Neural Network (CNN) normally and the distributed learning, and this was done using the Raspberry Pi open-source hardware platform, the system that is low-cost and highly scalable in terms of sensor devices type and the number of sensor nodes, which makes them well suited to a wide range of applications related to environmental monitoring, the sensors device have been connected to hardware and software design. Some software components, such as operating systems, sensor/hardware drivers, may need development. In the proposed method, the amount of data is large because the result in the middle of the computation processing is sent and it can be predicted that the total computation processing time will be reduced because the computational processing handled by each node will be reduced by section processing. The concentration of energy consumption can also be suppressed because the proposed method achieves decentralization compared to performing all calculations with a single sensor.
The Single Diode Model for PV Characteristics Using Electrical Circuit
Authors: RASHEED Mohammed , SHIHAB Suha , RASHID Taha
Published: October 2023

A new algorithm of Two-Point Bracketing method based on Newton's algorithm has been developed. The order of convergence of the proposed algorithm is six. Starting with a suitably chosen x_0, this technique generates a sequence of iterations converging to the root. It requires evaluations of only one first order derivatives per iteration. The proposed method is comparable with NRM and does not need an evaluation derivative at the second order of the given function as required in other numerical methods. The efficiency of the technique is tested on a nonlinear equation of a model of a PV cell. It is observed that the proposed method needs lesser number of iterations than NRM.
Extraction of a Photovoltaic Cell's Single-Diode Model Parameters from Equivalent Circuit
Authors: RASHEED Mohammed , SHIHAB Suha , RASHID Taha
Published: October 2023

The algorithms are plays an important and significant rule in the evaluation of nonlinear equations. In this paper, two methods for solving a nonlinear equation of a solar cell including single diode model are presented. The solution is examined with different values of load resistance 1 to 5 Ω at room temperature. The nonlinear equation of a photovoltaic cell is calculated from the equivalent circuit of this cell. The obtained results reveal that the propose algorithm is appropriate one for solving such equations.
On NM-Hollow Modules
Authors: Hameed Firas N. , Kalaf Karim S.
Published: October 2023

This notion investigates the generalization of hollow module namely near maximal hollow module (NM-hollow module).  Any module M is NM-hollow if for every H  satisfy two properties namely nearly and maximal. Some new results have been studied and more relationships are presented.  The main result in this section is; if M is a faithful and multiplication over the ring R, then M is NM-hollow module. Also, a direct-sum of NM-hollow module is also NM-hollow.
Deep Learning Based On Different Methods For Text Summary: A Survey
Authors: Turky Saja Naeem , Ahmed AL-Jumaili Ahmed Sabah , Hasoun Rajaa K.
Published: October 2023

Abstract—in today's rapidly growing information age, text summary has become a critical and important instrument for help understanding text information. it is really hard for human beings to physically summarize huge textual documents also there is an abundance of text content available online. text summarization is an active research field that works on compressing large pieces of text into smaller texts that preserve relevant information. text summary classified as extractive or abstractive. methods of extractive summarization working by deciding important text sentences and choosing them as a summary. that method based only on sentences from the source text. methods of abstractive summarization aim to paraphrase important information in a new form like that of humans. text summary can be achieved using different deep learning techniques, such as: fuzzy logic, Convolutional Neural (CNN), transformers, neural network, reinforcement learning, etc. in the past three years, the research trend in text summarization has also undergone a slight change, where new trends have appeared that are trends that lead to enhancement, how to improve the efficiency of text summarization to obtain high accuracy. we have made several attempts in this paper to discuss the various techniques used on the basis of deep learning for text summary in these years and observe the new trends in the field of deep learning.
Predictor-Corrector Solutions for Nonlinear Equations
Authors: RASHEED Mohammed , SHIHAB Suha , RASHID Taha , Ali Yaseen Hadi
Published: October 2023

Two algorithms Predictor-Corrector [type 2] and Newton's algorithms are developed and applied to evaluate the approximate solution for nonlinear equation of a single diode model. All programs associated with the above algorithms are written in Matlab language. We have been that Predictor-Corrector [type 2] algorithm values are sufficiently accurate besides that going from NRM. Examples of a PV cell design are presented to illustrate this feature.
Compression Techniques for the JPEG Image Standard by Using Image Compression Algorithm
Authors: BRISAM AHMED A. , MOSA QUSAY O.
Published: October 2023

Because of the raising needs for transmitting images in computer, mobile milieus, the study in the area of compressing image maximized considerably. Compressing image plays a critical part in processing digital images. The essential concept of compressing data is to decrease the data correlation. Through employing Discrete Cosine Transform (DCT), the data in time field could be transmuted into the field of frequency. Due to the reduced sensitivity of human sight in higher frequency, I is possible to compress data of the image or video by overturning its high frequency constituents nonetheless do no alteration to the eye. When pictures move like in video, the data in three-dimnsional space includes spatial plane and time axis. Hence, beside decreasing spatial correlation, time correlation is needed to be decreased. A process is presented named Motion Estimation (ME). Moreover, we can substitute the image by a Motion Vector (MV) to decrease time correlation. Thus, the improvement of effective methods for image compression becomes essential. Through the study, we similarly present JPEG standard and MPEG standard that are reputed image and video compression standard, correspondingly.
The Dynamical Properties of Modified of Bogdanov Map
Authors: Al-Hilli Wafaa H. , Kamel Rehab Amer
Published: October 2023

In the work, we study the general properties of  modified of the Bogdanov map in the form  Fa,m,k .

        We prove it  has sensitive dependence  on initial conditions and positive  Lyapunov exponent with some conditions . So we give estimate of topological entropy of modified Bogdanov map .
Review Optimized Artificial Neural Network by Meta-Heuristic Algorithm and its Applications
Authors: Kadhim Noor Hassan , Mosa Dr. Qusay
Published: October 2023

A Meta-Heuristic Algorithms Optimization (MAHO) is inspired by nature. The Artificial neural network (ANN) has been shown to be successful in a variety of applications, including machine learning. ANNs were optimized using meta-optimization methods to enhance classification performance and predictions. The fundamental objective of combining a meta-heuristic algorithm (MHAO) with an artificial neural network (ANN) is to train the network to update the weights. The training would be speedier than with a standard ANN since it will use a meta-heuristic method with global optimal searching capability to avoid local minimum and will also optimize difficult problems. will discuss some of these meta-heuristic algorithms using ANN as they are applied to common data sets, as well as real-time specific classification and prediction experiences. In order to give researchers motivational insights into their own fields of application.
On topological spaces generated by graphs and vice versa
Authors: Ibraheem Tabark Q. , Nagim Alaa A.
Published: October 2023

The relationship between Graph Theory and Topological Space has recently  developed greatly ,   as researchers have  been  able to  find

solutions to some problems in daily life by transforming the problem

into a graph and then generating a topological space and thus facilita-

ting reading the problem and solving it. The researchers also studied

the generation of graph from topological spaces.In this article we will present two types of relations on the edges set that generate topolog-

ical spaces, and we will discuss some properties of this  topology, and

we will  study  discuss the method of  returning from  the  topological

space to the graphs through using previous relationships.
EEG Signals Classification based on mathematical selection and cosine similarity
Authors: Al-fraiji Safaa S. , Al-Shammary Dhiah
Published: October 2023

This paper presents a new electroencephalogram (EEG) signal classification using a fractal-cosine similarity approach for diagnosing epilepsy patients. The proposed system provides two designed models with PSO as an optimization technique and without optimization. A full classification design is achieved, including prepressing data by normalization, Particle Swarm Optimization (PSO) as optimization technique to reduce the features of EEG signals, Fractal metric computations, metric mapping, and cosine similarity for the final decision. This paper used the BONN university EEG dataset, which consists of five categories. The dataset was divided into four groups based on training set size and testing set size. First, we are used to the training and testing ratio of 90/10. The second case is 80/20, the third case is 70/30, and the final case is 60/40 respectively. The proposed model achieves high rates of accuracy up to 100%.
Semi-lossless Fractal MRI Image Compression Based on Fixed length Technique
Authors: Al-Salamee Baidaa A. , Al-Shammary Dhiah
Published: October 2023

Medical image compression plays an essential role to handle large amounts of data for communication and storage purposes. Fractal image compression is a potential lossy compression models with a resulting image that loses some of its information. However, health data communication usually cannot afford any lose for patients visual information. This paper proposes a new high efficiency semi-lossless fractal image compression method (SLFIC) based on fractal theory and fixed length technique. Technically, the resultant lossy fractals compressed image is analyzed and error in comparison with the original image is detected. Then, Fixed-length is developed to compress the detected errors and attached to the compressed image. In practice, a potential performance by the new developed model has been obtained in comparison with two other lossless models: ( Lion optimization algorithm (LOA) and Lempel Ziv Markov chain Algorithm (LZMA) with Linde–Buzo–Gray (LBG) (L2-LBG)) and(Neural Network Radial Basis Function (NNRBF)). Moreover, a high quality that has been obtained by the proposed system based on Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR).
Classification Enterococcus Faecium and Faecalis Bacteria Images using Bag of Features
Authors: Abbas Rabab Farhan
Published: October 2023

Many numerous genera of bacteria that have a foremost influence on human health. One of them is Enterococcus, which has numerous species excluding Faecium and Faecalis. It reasons many sicknesses such as the bowel inflammation bacteremia, urinary tract infection, wound inflammation and meningitis. In instruction to describe, the fitting antibiotic used to luxury these diseases, where the antibiotics use to inhibit Faecium bacteria different from Faecalis bacteria, it is necessary to determine the exact type of bacteria, especially that the two types Faecium and Faecalis are similar in shape to the extent large.

 The target of this research is to classify Enterococcus bacteria into Faecium and Faecalis by using Bag of features technique, which accomplished and tested on database of the two species bacteria. The development method that combines circular shift pixel images, discrete Rigelet transform and Bag of features method which gives a better result on the non-stationary signals, which are executed on the above technique and newly trained classifier functional on blood agar plated images.

 In biological methods, the biologists cultivate bacteria in blood agar plates to determine the type of bacteria where examined in the electron microscope by using the eyes to the dependence on the form of bacteria and often they need to re-implant the sample in other mediums in order to know the type of bacteria.  This requires the cost of media and chemical materials and time. The method used in this research, the input for the program is blood agar plates images only and the type of bacteria is directly and accurately, this means that the method adopted in the program reduces costs and effort in biological methods, thus, this research helps  biologists to be able to diagnose bacteria with less effort, cost and time.

 The results exposed that the enriched classification method stretches better classification results on samples used images, when the average accuracy in the training set and validation set by using Bag of feature method are (0.83 and 0.79) respectively, they were increased in the proposed method to (1.00 and 0.92) respectively.
Some Results in Fuzzy 2- Metric Space
Authors: Sabri Raghad I. , Mohammedali Mayada N. , Sadiq Fatema Ahmad
Published: October 2023

The notion of fuzzy 2-metric space and its essential features are initially examined in this study. Following that, the ideas of compact fuzzy2- metric space and fuzzy totally bounded space are discussed. Furthermore, the essential theorems relating to these concepts are established. In particular, we prove that a fuzzy 2- metric space which is compact must be complete.
A Survey for Lie Detection Methodology Using EEG Signal Processing
Authors: Mohammed Israa J. , George Dr. Loay E.
Published: October 2023

Electroencephalography (EEG) is a hot topic all around the world. EEG signals, a series of measurements taken using electrodes on the scalp, can indicate brain activity. They are more private, sensitive, and difficult to steal and recreate. EEG data are increasingly commonly employed in diagnosing brain illnesses and the field of Brain-Computer interfaces thanks to advancements in biomedical signal processing techniques (BCI). BCI is a brain-computer interface that uses electrical impulses from the brain to communicate. EEG signals are used to interpret the electrical activity of the brain. The electrical activity of the brain is read using EEG signals. Many studies are being conducted in many fields to benefit from this technology. Studying EEG gives a solid understanding of how brain signals function in various moods and activities. Lie detection is a new technology that is being used to combat crime. Traditionally, this has been accomplished by language analysis, face and body movement recognition, training observation, and voice stress analysis. EEG analysis provides a better understanding of brain activity thanks to advances in cognitive science and neuroscience. Deception identification has become a severe issue as crime has increased. Previous surveys have discussed numerous approaches supported with experimental outcomes and compared them. This paper addressed each direction and offered different sets of characteristics and electrodes, EEG signal preprocessing, feature extraction, feature selection, and classification. Also, it discusses many methods which may need some adjustments at each phase of brain signal processing for lie detection.
On WNQP – Submodules
Authors: Mohammadali Haibat K. , Hassan Hero J.
Published: October 2023

Our goals in this paper are to introduce many results of a WNQP submodules such as triple zero of WNQP submodules. Moreover, several characterization of WNQP Submodule in some types of modules such as (multiplication, content, and finitely generated) modules. Furthermore WNQP radical of submodule are discuses.
Solving Multi-Objectives Function with Release Dates Problem using Branch and Bound Methods
Authors: Daowd Omar osama , Chachan Hanan Ali , Daway Hazim G.
Published: October 2023

This research study focuses on solving a multi-objective job scheduling problem on a single machine. This problem involves the summation of four objective functions namely the total flow time ( ), tardiness ( ), earliness ( ), and late work ( ) of each of the n jobs with unequal release dates . This is formulated as . 

We present some special cases that yield optimal solutions. also, we propose a branch and bound algorithm in order to find the exact (optimal) solution for it, by derive and use a good lower, and using some heuristics methods to find the upper bound of seven including Gray Wolfe algorithm (GW), and Bat algorithm (BAT), this algorithm was given to find the optimal solution for problems of size up to 17 functions.
Statistical Analysis of Copper Doped Titanium Dioxide
Authors: RASHEED Mohammed
Published: October 2023

In this research, titanium dioxide and Al nanoparticles were purchased from a Chinese company, then the copper materials were added in three ratios that are (0, 1, 2, 3, and 5) wt.%. The use of dry press method through a hydraulic press from one direction, using a mold of diameter of 10 mm to obtain a ceramic compressed dimension that was firing at a temperature of 900 °C. The thermal conductivity is studied for all samples that include pure with the copper added proportions and compared between them when adding the proportions for copper the ratio of 2 wt.% is the highest conductivity among the used ratios. For the mechanical properties, which included the hardness when adding percentage from copper toTiO2 2 wt.% ratio showed is the highest hardness value between other ratios, the samples surface, taking surface pictures of the samples through an optical microscope.
Exponentially fitted Diagonally Implicit three-stage fifth-order RK Method for Solving ODEs.
Authors: Jaleel Nour W. , Fawzi Firas A.
Published: October 2023

The EDITRK5 method. which this paper derives. is an exponentially fitted diagonally implicit RK method for solving ODEs with the equation  With the help of the set functions and  for exponentially fitting problems. this strategy is designed to integrate precise initial value problems (IVPs). The primary frequency of the issue.   is used to increase the method's accuracy. The new approach For the purpose of solving IVPs using exponential functions as solutions. EDITRK5 is a novel three-stage five-order exponentially-fitted diagonally implicit method. When the same issue is reduced to the first-order framework of equations. which can be solved using traditional RK approaches. different forms of third-order ODEs must be constructed using the new system. and numerical comparisons must be made. The numerical results demonstrate that the new strategy is more effective than methods that have already been published.
Classification and Diseases Identification of Mango Based on Artificial Intelligence: A Review
Authors: Hassoon Israa Mohammed
Published: October 2023

Mango is a drupe fruit which plays an active role in the economy of different countries. Classification process is a fundamental process in: diseases detection domain, sorting and grading. Previously, farmers can detect mango's diseases, identification ripe and unripe mango by their eyes, but it is inaccurate, waste of time and effort. AI technology helping farmers get high quality agricultural crops, the essential idea of AI in agriculture is its flexibility, reliability, speedy performance and applicability. AI technology improves enterprise performance and productivity by automating processes or tasks that once required human skill. AI can also understand data on a scale that no human can achieve, this ability can bring great advantages in the field of agriculture. In this paper, a review for application of artificial intelligence in mango classification and mango diseases identification have been presented.
Finger knuckle recognition, a review on prospects and challenges based on PolyU dataset
Authors: AL-Janabi Dua'a Hamed , AL-Juboori Ali Mohsin
Published: October 2023

In the previous few years, Finger knuckle (Fk) has received a lot of interest as a biometric trait in recent years. It will provide economic human identification performance due to its distinct difference between human-specific alternatives of visible lines, wrinkles, and ridges spread on the surface external of all finger knuckles. The foundation for most biometric systems is Fks. This report presents a thorough analysis of the pertinent Finger knuckle investigations. The foundation for most biometric systems is Fks. The identification system through finger knuckles usually contents of 4 steps, specifically image Acquisition, image preprocessing, feature extraction, and have matched. There are numerous methods used during this research at each level. The paper is likely to highlight these methods used in the PolyU database
Using Numerical Methods and Graph Theory for Developing Mathematical Models to Estimate Uranium Concentrations
Authors: Yaseen Suha K. , Arif Ghassan E. , Khalef Nihad Sh.
Published: October 2023

The research aims to build sports models to find the concentration of uranium in herbs using twelve herbs from medicinal herbs various uses by human use crime methods theory definition and some numerical methods different like Novel and Hermitian where we got mathematical models implicitly through it effect amount uranium herbs, and we got on miniatures mistake percentage almost non-existent.