bluuebunny/crossref_metadata_2025 huggingface dataset:
Retrato dos Estudos Feministas, de Mulheres e de Gênero no Brasil (1971-2019): a consolidação do campo científico, aprendizados e desafios
Authors: Hoppen Natascha Helena Franz , Dalmaso-Junqueira Bruna
Published: August 2023

Objetivo: Discutir a consolidação dos Estudos Feministas, de Mulheres e de Gênero (EF) como campo científico no Brasil; identificar intersecções sociais e acadêmicas entre o contexto histórico e político de lutas feministas e os avanços científicos que dele se desdobram; problematizar desafios a serem superados na produção do campo.
Método: Em abordagem quanti-qualitativa, parte-se de análises métricas de artigos brasileiros publicados entre 1971 e 2019 e indexados na base de dados 1Findr, dando ênfase às principais palavras-chave que tematizaram as pesquisas desenvolvidas no campo ao longo de cada década. Buscando complexificar a análise da ciência produzida nos EF, costuramos seus próprios saberes à discussão cientométrica.
Resultados: Constatou-se: (a) consonância dos movimentos científicos com aqueles de fora das universidades ao longo das décadas; (b) limitações dos feminismos liberais, brancos e eurocêntricos ainda hoje persistentes; (c) proeminência dos feminismos plurais – notadamente do feminismo negro – e das coalizões estratégicas possíveis; (d) relevância da inserção do movimento LGBTQIA+ no campo.
Conclusões: A produção acadêmica dos EF é uma conquista do próprio movimento social que lhes dá origem e reflete suas potencialidades e limitações em relação a seus sujeitos políticos. Destaca-se o caráter exponencial do crescimento da produção interdisciplinar interessada na perspectiva feminista, de mulheres e de gênero na ciência brasileira, embora ainda haja relevantes desafios e lacunas. Como tarefa urgente, indica-se a necessidade de incorporação de uma perspectiva plural, interseccional e relacional à pesquisa na área, que combata narrativas hegemônicas e homogeneizantes também dentro de um movimento social e científico de resistência.
Notas para uma teoria crítica discursiva da informação
Authors: Montenegro de Lima Clovis Ricardo , Gonçalves Márcio , Rebelo Maia Mariangela
Published: August 2023

Objetivo: o artigo apresenta anotações iniciais para uma teoria crítica discursiva da informação.
Método: a teoria parte de Habermas, que considera o Discurso uma forma especial de Agir Comunicativo para construção de entendimento intersubjetivo. O Discurso é o meio que os sujeitos usam para resolver conflitos sobre algo no mundo, e para construir acordos teóricos e práticos. O Discurso entre sujeitos tem função de validação pragmática de expressões e representações do mundo da vida. Habermas observa que acordos por argumentos devem ter correspondência com o mundo objetivo.
Resultado: a partir desses pressupostos se faz o esboço de uma teoria crítica da informação. A informação é construção de significado e representação, mas é também acordo intersubjetivo sobre algo que existe no mundo.
Conclusões: assim, não existe informação fora, antes ou depois da comunicação. A informação faz parte da comunicação, nas interações mediadas pela linguagem.
Analisis Kepuasan Penghuni Kost Mahasiswa Di Lingkungan Universitas Ngudi Waluyo Menggunakan Algoritma C4.5
Authors: Ramadhan Krisna Cahya , Sipayung Yoannes Romando
Published: August 2023

Penelitian ini bertujuan untuk mengukur kepuasan mahasiswa terhadap kost atau kontrak. Untuk mencapai tujuan tersebut, penulis mengimplementasikan algoritma C4.5 dalam analisis data. Data kepuasan mahasiswa diambil melalui survei yang mencakup berbagai faktor terkait harga, fasilitas, tata letak yang strategis, dan kualitas dari kost atau kontrak tersebut. Algoritma C4.5 digunakan untuk menghasilkan model pengambilan keputusan berdasarkan kriteria yang relevan dengan tingkat kepuasan mahasiswa. Hasil dari model ini memberikan informasi yang berharga dalam memahami faktor-faktor apa yang paling mempengaruhi kepuasan mahasiswa terhadap kost atau kontrak. Hasil penelitian menunjukkan bahwa algoritma C4.5 berhasil membangun model yang mampu mengklasifikasikan tingkat kepuasan mahasiswa terhadap kost atau kontrak dengan akurasi yang tinggi. Hasil penelitian ini diharapkan dapat membantu pihak kost atau kontrak untuk meningkatkan kepuasan mahasiswa. Selain itu, penelitian ini juga dapat menjadi landasan untuk penelitian lebih lanjut dalam bidang kepuasan mahasiswa dan penerapan algoritma C4.5 pada masalah-masalah serupa.
Media Pembelajaran Kitab Masailal Muhtadi Berbasis Multimedia
Authors: Azhar Al , Iqbal Muhammad , Najmuddin Najmuddin , Azmi Daril
Published: August 2023

Penelitian ini adalah untuk mengembangkan aplikasi pembelajaran kitab masailal berbasis multimedia menggunakan adobe flash cs 6 sebagai pendukung pembelajaran kitab masailal. Penelitian ini menggunakan pendekatan penelitian pengembangan (Research and Development). Tempat penelitian di TPQ Zakiyatul Athfal Mane Tunong. Obyek penelitian ini berupa aplikasi alat bantu pembelajaran kitab masailal berbasis multimedia menggunakan macromedia flash. Metode yang digunakan dalam pengumpulan data dilakukan melalui observasi dan wawancara. Metode yang digunakan untuk menganalisis data adalah dengan teknik analisis deskriptif kualitatif yang diungkapkan dalam uraian. Uji kelayakan yang dikembangkan aplikasi alat bantu pembelajaran kitab masailal berbasis multimedia menggunakan macromedia flash ini sangat layak digunakan, karena dapat digunakan menggunakan Hp Andoid.
Semantic Framework for Query Synthesised 3D Scene Rendering
Authors: Devi I Sri Gayathri , Gerald Sowmiya Sree S, Jerrick , Palanisamy Geetha
Published: August 2023

View synthesis allows the generation of new views of a scene given one or more images. Current methods rely on multiple input images, which are practically not feasible for such applications. While using a single image to create a 3D scene is difficult since it necessitates a solid understanding of 3D settings. To facilitate this, a complete scene understanding of a single-view image is performed using spatial feature extraction and depth map prediction. This work proposes a novel end-to-end model trained on real images without any ground-truth 3D information. The learned 3D features are exploited to render the 3D view. Further, on querying, the target view is generated using the Query network. The refinement network decodes the projected features to in-paint missing regions and generates a realistic output image. The model was trained on two datasets, namely RealEstate10K and KITTI, containing an indoor and outdoor scene.
A Befitting Single-Player Squash Program to Educate and Assist Disabled/Autistic People using Pose Estimation and Unity
Authors: Fung Lung Ngok , Andaya Moddwyn
Published: August 2023

The COVID pandemic has had a notable impact on sports education and exercise over the past few years [7]. Many students have lost access to physical education classes due to school closures or virtual instruction. This paper develops an application using pose estimation that allows users to experience a digital squash game that involves body movements on their phones or computers. Using post estimation, this application can track and identify player movements that let players control game avatars with their movements [8]. A crucial factor that deserves consideration is the degree of difficulty a game offers. The game has a bot as an opponent that can score points precisely. The game may make it easier for the player to move in the direction of the squash ball in order to lessen the challenge that the bot presents. In the experiment, the efficacy of post estimation was tested. In twenty-five swings, all swings were successfully accomplished. With the pandemic restricting access to public sports facilities and other fitness facilities, the application provides a convenient way to exercise from home and the opportunity to learn more about squash.
A Pose-Based Walking/Running Coach System for Cerebral Palsy Patients Using Artificial Intelligence and Computer Vision
Authors: Zhu Edward , Sun Yu
Published: August 2023

Cerebral palsy is a common motor disability that causes gait abnormalities. Clinical gait analysis is expensive and inaccessible. We investigated the research question: how can we create an affordable and effective method using AI to provide gait analysis data to cerebral palsy patients? Machine learning and computer vision were used to develop a gait analysis mobile application. The MediaPipe library extracted pose vectors from both patient and expert gait videos. KMeans algorithm was utilized to match frames and determine joint angle differences. Flutter was used to create a complete app for real-time tracking and feedback. The AI model was deployed in the cloud. This research presents an application of machine learning and computer vision in an accessible and accurate solution. The K-means algorithm showed high accuracy with an average silhouette score 0.514 for expert videos. MediaPipe output had a high 29.2FPS on average.
Verifiable Data Sharing Scheme for Dynamic Multi-Owner Setting
Authors: Zhao Jing , Su Qianqian
Published: August 2023

One of scenarios in data-sharing applications is that files are managed by multiple owners, and the list of file owners may change dynamically. However, most existing solutions to this problem rely on trusted third parties and have complicated signature permission processes, resulting in additional overhead. Therefore, we propose a verifiable data-sharing scheme (VDS-DM) that can support dynamic multi-owner scenarios. We introduce a management entity that combines linear secret-sharing technology, multi-owner signature generation, and an aggregation technique to allow multi-owner file sharing. Without the help of trusted third parties, VDS-DM can update file signatures for dynamically changing file owners, which helps save communication overhead. Moreover, users independently verify the integrity of files without resorting to a third party. We analyze the security of VDS-DM through a security game. Finally, we conduct enough simulation experiments and the outcomes of experimental demonstrate the feasibility of VDS-DM.
IoT in Practice: Investigating the Benefits and Challenges of IoT Adoption for the Sustainability of the Hospitality Sector
Authors: Kalsi Nick , Carroll Fiona , Minor Kasha , Platts Jon
Published: August 2023

Enhancing the sustainability of the hospitality sector with technology is essential to achieving growth whilstalso reducing the hotel’s impact on the environment. Indeed, the Internet of Things (IoT) concept has recently gained popularity as a new research topic in various industrial disciplines, including the hospitality industry. IoT is being seen and used to transform the hospitality industry for the newly desired sustainable growth. However, it is not all ‘smooth sailing’ as multiple challenges must be addressed by organisations in the hospitality industry when installing IoT. These challenges include cost, security, infrastructure and IoT protocols. Considering the diversity of IoT applications, the paper will examine IoT’s use in hotels whilst also highlighting the challenges hotels face when using IoT. In particular, it will cover the effect of cyber security, including IoT’s protocol layers, potential monitoring and sensor technologies.
Internet of Things Network Architecture and Security Challenges
Authors: R Ahmed Muhammad , Shihimi Ahmed Al , Myo Thirein , Baroomi Badar Al , Kaiser M Shamim
Published: August 2023

The Internet of Things (IoT) has transformed not only the way we communicate and operate our devices, but it has also brought us significant security challenges. A typical IoT network architecture consists of four levels: a device, a network, an application, and a service, each with its own security considerations. There are three types of IoT networks: Personal Area Networks (PANs), Local Area Networks (LANs), and Wide Area Networks (WANs). Each type has its own security requirements, so it is important to understand their particular security requirements. Several communication protocols that are used in IoT networks, like Wi-Fi and Bluetooth, are also susceptible to vulnerabilities that require the implementation of additional security measures. In addition to physical security challenges, there are numerous security challenges in the form of authentication, encryption, software vulnerabilities, DoS attacks, data privacy, and supply chain security. In order to deal with these challenges, we need to take a multi-layered approach that is comprised of physical, technical, and organizational measures. In this paper, we present an overview of IoT network architecture, along with an analysis of security challenges.
Soft Labels for Rapid Satellite Object Detection
Authors: Ciolino Matthew , Rosario Grant , Noever David
Published: August 2023

Soft labels in image classification are vector representations of an image's true classification. In this paper, we investigate soft labels in the context of satellite object detection. We propose using detections as the basis for a new dataset of soft labels. Much of the effort in creating a high-quality model is gathering and annotating the training data. If we could use a model to generate a dataset for us, we could not only rapidly create datasets, but also supplement existing open-source datasets. Using a subset of the xView dataset, we train a YOLOv5 model to detect cars, planes, and ships. We then use that model to generate soft labels for the second training set which we then train and compare to the original model. We show that soft labels can be used to train a model that is almost as accurate as a model trained on the original data.
A Helpful Mobile Application to Assist the Behaviors of Autistic People through Mini Games Created Using Unity
Authors: Huang Leon , Andaya Moddwyn
Published: August 2023

With proliferating rates of people being diagnosed with autism, it has rung the bell for immediate change [7]. In an effort to ring the bell louder — though minimalistically — this app was developed to make life easier for autistic kids through the refining of their comprehension skills, decision-making skills, and restrictive behaviors [8]. This was done through the making of minigames and an adventure story. Some minigames were designed to cater to the restrictive behaviors of autistic kids by making the games more engaging. Other games focused on improving comprehension skills, such as memory or vocabulary. The adventure game tested both comprehension and decision-making skills. Despite the app's positive impact, there were blind spots due to the complex nature of autism. The best solution was to continuously tinker with the app to ensure maximum compatibility with the autistic audience. Although autism is a difficult diagnosis to cure, such an app can assist in making the lives of autistic kids easier. With increasing rates of autism diagnosis, this app serves as a reminder of the need for more resources to cater to the growing population of autistic individuals [9].
ShootPro: An Interactive and Immersive Basketball Shooting Practice Assistance System using Artificial Intelligence and Computer Vision
Authors: Chen Yuetpang , Yang Lin , Chang Marisabel
Published: August 2023

Today, millions of people watch basketball like the NBA and many have a favorite player whom they admire [4]. Some even want to play the sport like their favorite star. However, for those who haven’t tried the sport before, basketball can be very difficult. For example, beginners can miss shots because their shooting form changes every time, but they don’t know that its changed, resulting in repeated misses as they don’t fix it. Also, some people don’t know what a “correct shot” looks like and therefore wouldn’t know how to improve their shots. This paper proposes a software to solve this problem. This software uses mediapipe poses, AI comparison, and cv2 to help users identify the problems above and fix them [5]. We applied our application to the realworld basketball court and conducted a qualitative evaluation of the approach. The results show that with the help of this application, basketball players shoot with a better accuracy and form.
Efficient Fair and Robust SPDZ-Like Multi-Party Computation
Authors: Wang Chung-Li
Published: August 2023

Effective multi-party computation protocols have been developed, but concerns regarding privacy and correctness persist. Classic results demonstrate that guaranteed output delivery can be achieved by assuming fairness and identifiable abort. However, if the majority is malicious, it is still challenging to design an efficient implementation that can deliver correct outputs while maintaining robustness and fairness. To address this issue, we have redesigned the secret-sharing mechanism and employed a semi-trusted third party (TTP) as the key manager to provide optimistic backup for output delivery. The verification and delivery procedures prevent the malicious parties from “stealing” the output, when there is at least one honest party. Furthermore, the TTP has no knowledge of output, so even if he is malicious and colluding, we only lose fairness. The decryption is needed only when misconduct is detected. Our scheme also enables identified abort for offline preprocessing, and the audit of the offline sub-protocols can be publicly performed, holding corrupted parties accountable before receiving private inputs. With fairness and identifiable abort, output delivery is guaranteed by excluding the cheaters.
How to use Classical Operation in Digital Bits to Simulate Quantum Bits for the RSA Cryptosystem
Authors: Wang Jun-Ya , Chang Xui-Chengn , Wang Hung-Ju
Published: August 2023

In quantum algorithm, the Shor's algorithm can find prime decomposition of very big numbers easily and break RSA encryption much faster and more efficiently than in the classical case. How to complicant the public key to slow down the speed and efficiency of Shor's algorithm to secure our RSA encryption scheme is main issue in this study. By using classical random simulation to operation as quantum bits to complicate the RSA cryptosystem, even Shor's algorithm can not to find prime decomposition of very big numbers n with qubits random simulation easily.
An Informational Hub that Utilizes Modern Application User Interfaces to Encourage Healthy Lifestyles
Authors: Jin Weibo , Liu Megan
Published: August 2023

The idea for this app is a platform for people and especially athletes to know proper dieting, exercising, and how to recover from workout-related accidents [2]. I had to go online and search up everything I needed to know and sometimes I would get false information from the wrong websites. Athletes should be able to see what is good for them to eat, what kinds of workouts they should do everyday, as well as how to recover from certain injuries that they may sustain. When the user logs in to the app they will see options that say recovery exercise news and nutrition pages that contain all the information they will need. The nutrition page will display some common good foods to eat and their data such as calories, carbs, and more. The exercises page will list several important exercises vital to a good workout. Lastly, the injury page, also referred to as the recovery page, will show users a picture of the human body and allow them to select certain parts of the body to read up on relevant information pertaining to injuries around that area [3]. I also made 2 experiments to help me know and fix the app’s blindspot, the first one is a survey i give to my friends to try my app and fill it out, the second one is i follow the workouts and foods on my app for one day and compare to american’s daily nutrition and workout plans.
Utilisation of Open Intent Recognition Models for Customer Support Intent Detection
Authors: Mohammad Rasheed , Favell Oliver , Shah Shariq , Cooper Emmett , Vakaj Edlira
Published: August 2023

Businesses have sought out new solutions to provide support and improve customer satisfaction as more products and services have become interconnected digitally. There is an inherent need for businesses to provide or outsource fast, efficient and knowledgeable support to remain competitive. Support solutions are also advancing with technologies, including use of social media, Artificial Intelligence (AI), Machine Learning (ML) and remote device connectivity to better support customers. Customer support operators are trained to utilise these technologies to provide better customer outreach and support for clients in remote areas. Interconnectivity of products and support systems provide businesses with potential international clients to expand their product market and business scale. This paper reports the possible AI applications in customer support, done in collaboration with the Knowledge Transfer Partnership (KTP) program between Birmingham City University and a company that handles customer service systems for businesses outsourcing customer support across a wide variety of business sectors. This study explored several approaches to accurately predict customers' intent using both labelled and unlabelled textual data. While some approaches showed promise in specific datasets, the search for a single, universally applicable approach continues. The development of separate pipelines for intent detection and discovery has led to improved accuracy rates in detecting known intents, while further work is required to improve the accuracy of intent discovery for unknown intents.
Aspect-Based Sentimental Analysis for Travellers’ Reviews
Authors: M Alaydaa Mohammed Saad , Li Jun , Jinkins Karl
Published: August 2023

Airport service quality evaluation is commonly found on social media, including Google Maps. This valuable for airport management in order to enhance the quality of services provided. However; prior studies either provide general review for topics discussed by travellers or provide sentimental value to tag the entire review without specifically mentioning the airport service that is behind such value. Accordingly; this work proposes using aspect based sentimental analysis in order to provide more detailed analysis for travellers’ reviews. This works applied aspect based sentimental analysis on data collected from Google Map about Dubai and Doha airports. The results provide tangible reasons to use aspect based sentimental analysis in order to understand more the travellers and spot airport services that are in need for improvement.
IoT Resource Allocation and Optimization Using Improved Reptile Search Algorithm
Authors: Kota Prabhakar Narasappa , Chopade Pravin Balaso , D. Jadhav Bhagvat , Ghate Pravin Marotrao , Chavan Shankar Dattatray
Published: August 2023

The Internet of Things (IoT) is a dispersed network system that connects the world through the Internet. The architecture of IoT consists of more gateways and resources which cannot be allocated in a manual process. The allocation of resources in IoT is a challenging process due to the higher consumption of energy and high latency rate. To overcome the challenges in existing works, this research introduced an Improved Reptile Search Algorithm (IRSA) to solve the optimization problem which occurs during the time of allocation resources among IoT networks. IRSA employs the methodology of levy flight and cross-over to update the candidate position and enhance the search speed in a single iteration. The proposed method consumes less energy and has low latency during data transmission from User equipment (UE) to the base station.IRSA has been compared with the existing Scalable Resource Allocation Framework (SRAF) and Improved Chaotic Firefly Algorithm (ICFA). The obtained experimental results show that the proposed IRSA attained better performance with an allocation rate of 96.40% which is comparatively higher than SRAF and ICFA with 92.40% and 91.67% respectively.
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utilization in Wireless Sensor Network
Authors: R Shanmugavalli , P Subashini
Published: August 2023

Maintaining the energy conservation is considered as an important approach to increase the lifetime of WSN. In fact, an energy reduction mechanism is considered as the main concept to enhance the lifespan of the network. In this paper, the performance analysis/evaluation of optimization technique, specifically, Ant Colony Optimization (ACO) and modified ACO (m-ACO) in the routing method are investigated. This network analysis is done by 100 iterations and differentiated with 50, 75 and 100 numbers of nodes. Finally, experimental results illustrate that the performance of m-ACO algorithm obtained the obvious performance, which is comparatively better than ACO algorithm, because it improves the routing efficiency by pheromone evaporation control and energy threshold value. It demonstrates that m-ACO algorithm gives better results than ACO in terms of throughput (1.41%), transmission delay (1.43%), packet delivery ratio (1.41%), energy consumption (2.05%), and the packet loss (9.70%). The convergence rate is analysed for ACO and m-ACO algorithms with respect to 100 number of iterations for WSNs.
Education Unit Strategies in Increasing Students' Interest in Participating in Religious Extracurricular Activities at School
Authors: Kristianto Heri , Susetyo Agus , Utama Ferdian , Fitriono Eko Nani , Jannah Siti Roudhotul
Published: August 2023

Education is a must for a nation because education is a way to educate the nation's life. The education process does not only take place formally but can also be obtained through organizations in schools. Organizationally in the school environment, there is a religious extracurricular, Rohis, which provides positive student activities. However, the right strategy is needed so that students are motivated to participate in a series of activities in religious extracurricular activities. So the problem formulation is how the education unit strategy to increase student interest in participating in Rohis religious extracurricular activities at school. This research was conducted at SMP N 9 Metro and using qualitative methodology: data were obtained through interviews with the education unit and extracurricular school administrators, observation, and documentation. The results of this study explain that convincing students of things according to their needs by using the advice method and providing guidance by encouraging students to understand and practice the teachings of Islam correctly by using the technique of exemplary, habituation, punishment, reward, and attention, encouraging students to understand and practice Iman, Islam, and Ihsan with actualization and application in daily life using the method of habituation, exemplary, and attention.

Keywords: Education Unit Strategies, Students' Interest, Religious Extracurricular
Lane Detection for Autonomous Driving in a Video Game Environment
Authors: GİRAY Ahmet Onur , DOĞAN Hatice
Published: August 2023

To ensure comfortable and safe driving, the automotive industry has accelerated the development of autonomous vehicles in recent years. In the design of autonomous vehicles, challenging problems such as lane detection need to be solved. Convolutional neural networks, which show superior performance in many fields, have also been used in the lane detection problem. The datasets required to train CNN models are too large to be collected and labeled by manual effort. In this study, a method is proposed to automatically collect a labeled data set from the video game environment to be used in the detection of highway lanes. Different CNN models such as ResNet50, VGG16, Xception, and InceptionV3 networks are trained using the Transfer Learning method with 745,823 collected images. The images captured by the front vehicle camera are used as input, the coordinates of the points in the left and right lane and the center of the lane in the 2D plane in front of the vehicle and the angle of the vehicle are used as outputs. The performances of these models are tested and compared on the images collected from a road not used in the training set. According to the performance comparisons, ResNet50 performs best.
KORELASI KEKERASAN BERBAGAI BAJA KOMERSIAL TERHADAP KEKASARAN PERMUKAAN YANG DIHASILKAN PADA PROSES GERINDA SILINDER KECEPATAN RENDAH TANPA PENDINGINAN
Authors: Isti Wahyu Isti Nugroho
Published: August 2023

Kualitas permukaan suatu produk logam pada pekerjaan pemesinan dipengaruhi oleh pemilihan proses, alat potong, dan pemilihan material yang dikerjakan. Beragam klasifikasi jenis baja dengan berbagai paduan untuk memperbaiki sifat dan mampu mesin baja. Proses pemesinan gerinda silinder digunakan untuk mencapai kualitas permukaan dan akurasi ukuran suatu pekerjaan.  Perlu dilakukan penelitian untuk mempelajari adanya korelasi karakteristik baja terhadap mampu mesin yang dimiliki supaya dapat menjadi referensi bagi pengguna untuk menentukan jenis baja terhadap hasil proses yang diharapkan. Penelitian ini bertujuan mengetahui apakah ada korelasi pada kekasaran permukaan yang dihasilkan pada pemesinan gerinda silinder terhadap sifat mekanik baja komersial. Diperoleh hasil semakin tinggi Feedrate akan semakin besar nilai kekasaran permukaan hasil gerinda. Karakteristik material dengan nilai kekerasan yang semakin tinggi akan menghasilkan kekasaran permukaan yang semakin rendah. Terdapat pengecualian korelasi karakteristik pemesinan terhadap sifat mekanik baja pada AISI D2 disebabkan unsur paduan krom yang tinggi.

 

Kata kunci: Kekasaran Permukaan, gerinda silinder
Analisis Pengendalian Kualitas Produk Pada Pt Djohartex Dengan Metode Statistical Process Control
Authors: Erwin Noer Wahyu Murti  , Ferida Yuamita
Published: August 2023

Permasalahan pada proses produksi PT Djohartex menimbulkan kerugian bagi perusahaan. Selama Juni hingga September 2022, tingkat kecacatan berada pada level yang relatif tinggi di 17%. sedangkan tingkat kecacatan yang diperbolehkan sebesar 15%, tingkat kecacatan yang tinggi akan mempengaruhi, salah satunya kenaikan biaya produksi. Diharapkan penelitian ini dapat mengurangi tingkat cacat produksi. Tingkat kecacatan produk memiliki banyak penyebab seperti kualitas bahan baku, human error dan keadaan peralatan yang sudah tidak baik mempengaruhi produktifitas serta produk itu sendiri. Penggunakan metode SPC diharapkan dapat mengurangi tingkat defect, jenis kerusakan dan mengkategorikan pengaruh cacat produk. Memungkinkan identifikasi kerusakan dan faktor-faktor yang berdampak besar terhadap cacat produk. Dari pengolahan diagram pareto persentase terbesar adalah cacat rapat/renggang dengan persentase 31.41%, cacat pakan kendor 15.67%, serta cacat baar 15.90%. Pengolahan diagram kontrol diperoleh hasil CL 0.17231, LCL 0.21, serta UCL 0.1345. Dari data tersebut diketahui proses produksi PT. Djohartex tidak melewati garis batas yang sudah ditentukan. Berdasarkan diagram fishbone jenis cacat memiliki 3 faktor utama yaitu manusia, kurangnya pengecekan proses produksi, mesin mengalami rubber strip, beam aus hingga sensor mati, dan bahan baku terjadi kanji berkerak dan benang rapuh. Perbaikan faktor manusia melakukan pengawasan, faktor mesin melakukan maintenance teratur, faktor bahan baku melakukan pengecekan benang yang digunakan.
USULAN PERBAIKAN KECELAKAAN KERJA PADA PROSES PENCETAKAN PT MEGA JAYA LOGAM MENGGUNAKAN JSA DAN FTA
Authors: Pulung Akbar Mukti Mulyojati  , Ferida Yuamita
Published: August 2023

PT. Mega Jaya Logam merupakan salah satu industri manufaktur yang berfokus pada bidang industri pengecoran logam dan permesinan. Produk-produk yang dihasilkan pada industri ini antara lain berupa kursi taman antik, manhole cover, tiang lampu antik, grill tangkapan air, dan masih banyak lagi. Dalam proses pembuatan produknya, PT. Mega Jaya Logam menggunakan mesin tanur induksi untuk meleburkan logam yang kemudian akan diikuti tahapan penuangan logam panas dalam cetakan. Pada bagian pencetakan pernah didapati kecelakaan kerja yang dimana kecelakaan ini lebih tinggi dari beberapa departemen yang ada pada PT. Mega Jaya Logam seperti terkena serpihan logam & terkena percikan logam panas yang berdampak terhadap para pekerja. Tujuan dari penelitian ini untuk mengetahui faktor penyebab kecelakaan serta mencari potensi dan risiko yang didapat menggunakan metode Job Safety Analysis (JSA) lalu menganalisis serta mencocokkan potensi bahaya yang didapat dengan beberapa faktor yang membuat para pekerja mendapati kecelakaan kerja yang dicari menggunakan Fault Tree Analysis (FTA) yang kemudian diberikan usulan bagaimana upaya pengendalian dengan metode agar meminimalisir kecelakaan kerja di masa mendatang.
Long-term reduction in CO2 emissions from the Elbe River due to water quality improvement
Authors: Tian Mingyang , Hartmann Jens , Romero-Mujalli Gibran , Amann Thorben , Ran Lishan , Park Ji-Hyung
Published: August 2023

Abstract. Polluted rivers transport and transform large quantities of anthropogenically-derived organic carbon to coastal regions, and account for an unneglectable share of global CO2 emissions. Effective river water management can enhance water quality and reduce CO2 emissions from the surface water to the atmosphere. However, the effect of water management on future riverine CO2 emissions remains a topic yet to be explored. In this context, the effects of water quality on riverine carbon dynamics were evaluated by examining the temporal variations in carbon fluxes from the Elbe River during a climate base period (around 30 years) from 1984 to 2018. The analysis of long-term data reveals that annual CO2 emissions from the Elbe River have decreased from 3.8±1.7 Tg C yr–1 in 1984 to 1.3±0.6 Tg C yr–1 in 2018 (1 T = 1012), and the largest reduction occurred after the initial decade of reunification of Germany. The changes in wastewater treatment have largely reduced nutrient loads, mitigated eutrophication, impacted the quality of the transported carbon to the ocean, resulting in concurrent decreases in CO2 emissions. The long-term trends in the Elbe River underscore the importance of water quality management for mitigating CO2 emissions from polluted rivers around the globe.
The community-centered aquatic biogeochemistry model unified RIVE v1.0: a unified version for water column
Authors: Wang Shuaitao , Thieu Vincent , Billen Gilles , Garnier Josette , Silvestre Marie , Marescaux Audrey , Yan Xingcheng , Flipo Nicolas
Published: August 2023

Abstract. Research on mechanisms of organic matter degradation, bacterial activities, phytoplankton dynamics, and other processes has led to the development of numerous sophisticated water quality models since one of the first in 1925, based on first order kinetics for organic matter degradation. The community-centered aquatic biogeochemistry model RIVE was initially developed in 1994 and has since been integrated into several software programs such as Seneque-Riverstrahler, pyNuts-Riverstrahler, ProSe/ProSe-PA and Barman. After 30 years of research, the use of different programming languages including Qbasic, Visual Basic, Fortran, ANSI C and Python, as well as parallel evolution and the addition of new formalisms, raise questions about their comparability. This paper presents a unified version of the RIVE model for the water column, including formalisms for bacterial communities (heterotrophic and nitrifying), primary producers, zooplankton, nutrients, inorganic carbon, and dissolved oxygen cycles. The unified RIVE model is open source and implemented in Python 3 to create pyRIVE 1.0, and in ANSI C to create C-RIVE 0.32. The organic matter degradation module is validated by simulating batch experiments. The comparability of the pyRIVE 1.0 and C-RIVE 0.32 softwares is verified by modeling a river stretch case study, which considers the full biogeochemical cycles (microorganisms, nutrients, carbon, and oxygen) in the water column, as well as the effects of light and water temperature. The results show that the simulated concentrations of all state variables, including microorganisms and chemical species, are very similar for pyRIVE 1.0 and C-RIVE 0.32. This open-source project highly encourages contributions from the aquatic biogeochemistry community to further advance the project and achieve common objectives.
SPATIO-TEMPORAL ANALYSIS OF THE EFFECTS OF URBAN GROWTH ON URBAN HEAT ISLAND: CASE OF KONYA, TURKIYE
Authors: Akdeniz H. B.
Published: August 2023

Abstract. The increase in impermeable surfaces within the urban areas contributes to local and regional-scale climate changes. This phenomenon, called "Urban Heat Island," is observed as the temperature in urban areas is higher than rural areas and natural landscape areas on the urban fringe. In recent years, advances in remote sensing and geographic information system technologies have enabled the urban heat island effect to be determined more quickly, economically, and accurately. In this study, the rapidly increasing urbanization in Konya, Türkiye and the resulting urban heat island effect have been analyzed. The study consists of four steps. In the first step, land surface temperatures for 1990 and 2022 of Konya city center were determined using the thermal band of Landsat-5 TM and Landsat-8 OLI satellite images. Then, satellite images were classified using the maximum likelihood method to determine land use and land cover in Konya. The effects of land use types and urban growth on urban heat island were examined. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-Up Index (NDBI) analyses were examined the statistical relationships between land surface temperature. The last step, the urban heat island effects of different types of regions in the city center of Konya were determined based on their urban form, texture, structure, landscape, and planning strategy. As a result of the study, measures that can be taken especially in spatial planning and design policies have been identified to reduce and prevent the urban heat island in Konya.
DEEP LEARNING BASED AERIAL IMAGERY CLASSIFICATION FOR TREE SPECIES IDENTIFICATION
Authors: Bayrak O. C. , Erdem F. , Uzar M.
Published: August 2023

Abstract. Forest monitoring and tree species categorization has a vital importance in terms of biodiversity conservation, ecosystem health assessment, climate change mitigation, and sustainable resource management. Due to large-scale coverage of forest areas, remote sensing technology plays a crucial role in the monitoring of forest areas by timely and regular data acquisition, multi-spectral and multi-temporal analysis, non-invasive data collection, accessibility and cost-effectiveness. High-resolution satellite and airborne remote sensing technologies have supplied image data with rich spatial, color, and texture information. Nowadays, deep learning models are commonly utilized in image classification, object recognition, and semantic segmentation applications in remote sensing and forest monitoring as well. We, in this study, selected a popular CNN and object detection algorithm YOLOv8 variants for tree species classification from aerial images of TreeSatAI benchmark. Our results showed that YOLOv8-l outperformed benchmark’s initial release results, and other YOLOv8 variants with 71,55% and 72,70% for weighted and micro averaging scores, respectively.
FREQUENCY RATIO ASSESSMENT FOR LANDSLIDES TRIGGERED BY 6 FEBRUARY 2023 KAHRAMANMARAS TURKIYE EARTHQUAKES BETWEEN GOLBASI AND ERKENEK
Authors: Cetinkaya S. , Tunar Ozcan N. , Karakas G. , Karakas V. E. , Kocaman S. , Gokceoglu C.
Published: August 2023

Abstract. Landslides triggered by earthquakes are significant geological hazards that can have devastating consequences, posing risks to human lives, infrastructure, and the environment. These seismic events may cause the instability of slopes and result in the displacement of soil and rock materials, leading to landslides. It is crucial to understand the characteristics and mechanisms of earthquake-triggered landslides in order to effectively manage and mitigate their associated risks. The number of landslides triggered by the 2023 Kahramanmaraş earthquakes (with magnitudes of 7.7 and 7.6) was over three thousand and their destructive effects were also devastating as secondary hazards. This study aims to examine the characteristics of landslides using the frequency ratio (FR) model. A landslide susceptibility map (LSM) was also produced using the output. For this purpose, in this study, we derived landslides triggered by the earthquakes in a part of the earthquake-affected region, between Golbasi town of Adiyaman and Erkenek village of Malatya covering an area with a size of 625 km2. The study utilized a landslide inventory that was manually delineated by visual interpretation based on pre-event and post-event. These associations can serve as a foundation for the application of various data-driven machine learning techniques. The findings of this study will contribute to the development of accurate LSMs, providing crucial insights into the behavior of earthquake-triggered landslides.
ASSESSING THE IMPACT OF BEET WEBWORM MOTHS ON SUNFLOWER FIELDS USING MULTITEMPORAL SENTINEL-2 SATELLITE IMAGERY AND VEGETATION INDICES
Authors: Kara S. , Maden B. , Ercan B. S. , Sunar F. , Aysal T. , Saglam O.
Published: August 2023

Abstract. Remote sensing technology plays a crucial role in detecting and monitoring environmental issues, offering the ability to monitor large areas, diagnose problems early, and facilitate accurate interventions. By integrating in-situ data with qualitative measurements obtained from satellite images, comprehensive insights can be obtained, and statistical inferences can be established. This study focuses on analyzing the damages caused by beet webworm moths (Loxostege sticticalis) in sunflower fields located in the Ortaca neighborhood of Tekirdağ province in Thrace region, utilizing Sentinel-2 satellite images and in-situ data collected from the sunflower fields in Ortaca. The relationship between different spectral indices, such as the Enhanced Vegetation Index, Chlorophyll Index Green, and spectral transformation techniques like Tasseled Cap Greenness, derived from Sentinel-2 satellite images, and the observed damage rates in various sunflower fields' in-situ data was investigated. The results revealed a negative correlation between the variables, highlighting EVI as the most effective indicator of damage among the plant indices. Leveraging these findings, a damage map was generated using EVI, enabling visual interpretation of the damage status in other sunflower fields within the study area. These findings offer valuable insights into the impact of pests on sunflower crops, despite the accuracy evaluation results falling below the desired level, with an overall accuracy of 75% and a Kappa accuracy of 65%, attributed to the limited availability of in-situ data.
Performance of the cross-polarization experiment in conditions of radiofrequency field inhomogeneity and slow to ultrafast magic angle spinning (MAS)
Authors: Šmelko Andrej , Blahut Jan , Reif Bernd , Tošner Zdeněk
Published: August 2023

Abstract. In this paper, we provide an analytical description of the performance of the cross-polarization (CP) experiment, including linear ramps and
adiabatic tangential sweeps, using effective Hamiltonians and simple rotations in 3D space. It is shown that radiofrequency field inhomogeneity
induces a reduction in the transfer efficiency at increasing magic angle spinning (MAS) frequencies for both the ramp and the adiabatic CP experiments. The effect depends
on the ratio of the dipolar coupling constant and the sample rotation frequency. In particular, our simulations show that for small dipolar
couplings (1 kHz) and ultrafast MAS (above 100 kHz) the transfer efficiency is below 40 % when extended contact times up to
20 ms are used and relaxation losses are ignored. New recoupling and magnetization transfer techniques that are designed explicitly to
account for inhomogeneous radiofrequency fields are needed.
A long-term proxy for sea ice thickness in the Canadian Arctic: 1996–2020
Authors: Glissenaar Isolde A. , Landy Jack C. , Babb David G. , Dawson Geoffrey J. , Howell Stephen E. L.
Published: August 2023

Abstract. This study presents a long-term winter sea ice thickness proxy product for the Canadian Arctic based on a random forest regression model – applied to ice charts and scatterometer data, trained on CryoSat-2 observations, and applying an ice type–sea ice thickness correction using the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) – that provides 25 years of sea ice thickness in the Beaufort Sea, Baffin Bay, and, for the first time, the Canadian Arctic Archipelago. An evaluation of the product with in situ sea ice thickness measurements shows that the presented sea ice thickness proxy product correctly estimates the magnitudes of the ice thickness and accurately captures spatial and temporal variability. The product estimates sea ice thickness within 30 to 50 cm uncertainty from the model. The sea ice thickness proxy product shows that sea ice is thinning over most of the Canadian Arctic, with a mean trend of −0.82 cm yr−1 in April over the whole study area (corresponding to 21 cm thinning over the 25-year record), but that trends vary locally. The Beaufort Sea and Baffin Bay show significant negative trends during all months, though with peaks in November (−2.8 cm yr−1) and April (−1.5 cm yr−1), respectively. The Parry Channel, which is part of the Northwest Passage and relevant for shipping, shows significant thinning in autumn. The sea ice thickness proxy product provides, for the first time, the opportunity to study long-term trends and variability in sea ice thickness in the Canadian Arctic, including the narrow channels in the Canadian Arctic Archipelago.
Impact of Compulsory Citizenship Behavior on Employee Performance: A Mediating Role of Perceived Insider Status and Moderating Role of Psychological Hardiness
Authors: Muhammad Awais Ahmed  , Ishaque Amir
Published: August 2023

The current study investigates the relationship between compulsory citizenship behavior (CCB) and employee performance (EP) through the underlying mechanism of perceived insider status (PIS) and the moderating effect of psychological hardiness (PH). For this purpose, data were collected through a non-probability convenience sampling technique in three-time lags from 376 employees working in hotels located in Pakistan. The results support the effect of compulsory citizenship behavior on employee performance, directly and indirectly, through the perceived insider status of employees. Results also support the moderating role of psychological Hardiness weakening the negative relationship between CCB and perceived insider status.
Interdisciplinary Oral Rehabilitation of a Teenage Patient with Down Syndrome: A Case Report
Authors: ARDA SÖZÜÖZ Melis , ERDOĞAN Melek Almıla , KALYONCUOĞLU Ülkü Tuğba , AKSOY Merve
Published: August 2023

Abstract
This case report aimed to share the dental rehabilitation of a teenage patient with Down Syndrome who applied to our clinic with aesthetic complaints and to provide a guide to dentists on the treatment options of young syndromic patients with various dental problems.The clinical and radiographic examination of a 17-year-old male patient with Down Syndrome, who applied to the University of Health Sciences, Gülhane Department of Prosthodontics, with aesthetic complaints, revealed the necessity of occlusion regulation and the restoration of the existing teeth. Aesthetic need was taken into consideration and a treatment plan was made with the Department of Pediatric Dentistry.
After the extraction of the patient's hopeless teeth, the missing teeth were corrected with a fixed partial denture, taking into account the patient's wishes. Onlay restorations made of 3D printed resins are planned for teeth that remain in infraocclusion. It was planned to restore anterior maxillary teethwith strip crowns in order to achieve aesthetics, and after the root canal treatment Finally, premolar forms were created for the maxillary permanent canine teeth with strip crowns to support the occlusion.The treatment of our patient was completed, and his function and phonation were maintained, as well as achieving the aesthetic he dreamed of.