bluuebunny/crossref_metadata_2025 huggingface dataset:
Sustainable Development and National Integration: A Catalyst for Enhancing Environmental Law Compliance in Nigeria
Authors: Olujobi Olusola Joshua , Irumekhai Oshobugie Suleiman , Aina-Pelemo Adetutu Deborah
Published: April 2024

This study delves into the pivotal roles played by sustainable development and national integration in advancing legal compliance, environmental protection, and sustainability within Nigeria. Employing a doctrinal and conceptual legal research approach, it meticulously examines pertinent literature, international exemplars, and conducts an exhaustive analysis of primary and secondary legal sources, including the 1999 Constitution of the Federal Republic of Nigeria (as amended), the Climate Change Act of 2021, and relevant international instruments. An effort has been made to examine extant sustainable development practices, presenting an encompassing snapshot of the nation’s legal, environmental, and sustainability apprehensions, while also addressing the attendant challenges. Moreover, it undertakes a comprehensive evaluation of Nigeria’s prevailing legal framework concerning environmental protection, delving into its potential for long-term sustainability. The findings resoundingly underscore the potency of sustainable development as a strategic avenue for achieving legal compliance, environmental protection, and enduring sustainability. Importantly, the study unveils that the Sustainable Development Goals (SDGs) find manifestation within Chapter II of the Constitution, albeit in a non-justiciable form, thereby impeding the stride toward their attainment. Nevertheless, it accentuates the necessity for an approach that meticulously factors in Nigeria’s distinctive context and specific requisites, thereby fostering effectiveness through national integration, policy execution, effective communication, and collaborative synergy across stakeholders within both the public and private domains. Essential to the realization of SDGs’ objectives is a synergistic collaboration amongst the government, academia, and non-governmental organizations. This study illuminates the latent potential of sustainable development and national integration as efficacious strategies for propelling legal compliance, environmental protection, and sustainability. It proffers a recommendation for the assimilation of innovative paradigms that have proven successful in mitigating environmental degradation elsewhere. Ultimately, the study ardently advocates for comprehensive overhauls to systematically address Nigeria’s complex entanglements encompassing legality, environment, and sustainability. Furthermore, the study ardently champions the elimination of the provision stipulated in section 6(6)(c) of the 1999 Constitution as a crucial step towards realizing the SDGs’ objectives within Nigeria.
Multi-label classification with imbalanced classes by fuzzy deep neural networks
Authors: Succetti Federico , Rosato Antonello , Panella Massimo
Published: April 2024

Multi-label classification is an advantageous technique for managing uncertainty in classification problems where each data instance is associated with several labels simultaneously. Such situations are frequent in real-world scenarios, where decisions rely on imprecise or noisy data and adaptable classification methods are preferred. However, the problem of class imbalance represents a common characteristic of several multi-label datasets, in which the distribution of samples and their corresponding labels is non-uniform across the data space. In this paper, we propose a multi-label classification approach utilizing fuzzy logic in order to deal with the class imbalance problem. To eliminate the need for an expert to determine the logical rules of inference, deep neural networks are adopted, which have proven to be exceptionally effective for such problems. By combining both fuzzy inference systems and deep neural networks, the strengths and weaknesses of each approach can be mitigated. As a further development, a symbolic representation of time series is put in place to reduce data dimensionality and speed up the training procedure. This allows for more flexibility in model application, in particular with respect to time constraints arising from the causality of observed time series. Tests carried out on a multi-label classification dataset related to the current and voltage profiles of several household appliances show that the proposed model outperforms four baseline models for time series classification.
Online course evaluation model based on graph auto-encoder
Authors: Yuan Wei , Zhao Shiyu , Wang Li , Cai Lijia , Zhang Yong
Published: April 2024

In the post-epidemic era, online learning has gained increasing attention due to the advancements in information and big data technology, leading to large-scale online course data with various student behaviors. Online data mining has become a popular and important way of extracting valuable insights from large amounts of data. However, previous online course analysis methods often focused on individual aspects of the data and neglected the correlation among the large-scale learning behavior data, which can lead to an incomplete understanding of the overall learning behavior and patterns within the online course. To solve the problems, this paper proposes an online course evaluation model based on a graph auto-encoder. In our method, the features of collected online course data are used to construct K-Nearest Neighbor(KNN) graphs to represent the association among the courses. Then the variational graph auto-encoder(VGAE) is introduced to learn the useful implicit features. Finally, we feed the learned implicit features into unsupervised and semi-supervised downstream tasks for online course evaluation, respectively. We conduct experiments on two datasets. In the clustering task, our method showed a more than tenfold increase in the Calinski-Harabasz index compared to unoptimized features, demonstrating significant structural distinction and group coherence. In the classification task, compared to traditional methods, our model exhibited an overall performance improvement of about 10%, indicating its effectiveness in handling complex network data.
Cluster analysis via projection onto convex sets
Authors: Tran Le-Anh , Kwon Daehyun , Deberneh Henock Mamo , Park Dong-Chul
Published: April 2024

This paper proposes a data clustering algorithm that is inspired by the prominent convergence property of the Projection onto Convex Sets (POCS) method, termed the POCS-based clustering algorithm. For disjoint convex sets, the form of simultaneous projections of the POCS method can result in a minimum mean square error solution. Relying on this important property, the proposed POCS-based clustering algorithm treats each data point as a convex set and simultaneously projects the cluster prototypes onto respective member data points, the projections are convexly combined via adaptive weight values in order to minimize a predefined objective function for data clustering purposes. The performance of the proposed POCS-based clustering algorithm has been verified through a large scale of experiments and data sets. The experimental results have shown that the proposed POCS-based algorithm is competitive in terms of both effectiveness and efficiency against some of the prevailing clustering approaches such as the K-Means/K-Means+⁣+ and Fuzzy C-Means (FCM) algorithms. Based on extensive comparisons and analyses, we can confirm the validity of the proposed POCS-based clustering algorithm for practical purposes.
An AutoML-based approach for automatic traffic incident detection in smart cities
Authors: Gkioka Georgia , Dominguez Monica , Mentzas Gregoris
Published: April 2024

In the realm of modern urban mobility, automatic incident detection is a critical element of intelligent transportation systems (ITS), since the ability to promptly identify unexpected events allows for quick implementation of preventive measures and efficient response to the situations as they arise. With the growing availability of traffic data, Machine Learning (ML) has become a vital tool for enhancing traditional incident detection methods. Automated machine-learning (AutoML) techniques present a promising solution by streamlining the machine-learning process; however the application of AutoML for incident detection has not been widely explored in scientific research In this paper, we propose and apply an AutoML-based methodology for traffic incident detection and compare it with state-ofthe-art ML approaches. Our approach integrates data preprocessing with AutoML, and uses Tree-based Pipeline Optimization Tool (TPOT) to refine the process from raw data to prediction. We have tested the efficiency of our approach in two major European cities, Athens and Antwerp. Finally, we present the limitations of our work and outline recommendations for application of AutoML in the incident detection task and potentially in other domains.
Could the Historical Transition from Segmented to Monophasic Sleep Explain the Modern Insurgence of Alzheimer’s Disease and Related Dementias?
Authors: Bragazzi Nicola Luigi , Boulares Ayoub , Garbarino Sergio
Published: April 2024

In their article, Finch and Burstein explore the hypothesis that Alzheimer’s disease and related dementias (ADRD) may predominantly be phenomena of the modern era. Through a review of classical Greek and Latin literature, they found minimal reference to conditions akin to ADRD, suggesting a historical rarity of severe cognitive decline. Instead, ancient texts focused on physical aspects of aging, with cognitive changes, when noted, not resembling modern-day dementia. Finch and Burstein further extend their analysis by drawing parallels with the Tsimane people of Bolivia, known for their low prevalence of dementia and cardiovascular diseases, attributed to lifestyle factors such as diet and physical activity. By comparing historical sleep patterns transitioning from segmented to monophasic sleep with those of the Tsimane community, we enriched Finch and Burstein’s research, highlighting the need to take into account a range of diverse factors, including sleep, in understanding the etiopathogenesis of ADRD in today’s society.
A meta-optimizer based on the upper confidence bound algorithm and orthogonal arrays: A preliminary empirical study
Authors: Cosío-León M.A. , Martínez-Vargas Anabel , Rodríguez-Cortés Gabriela
Published: April 2024

It is well-known that tuning a metaheuristic is a critical task because the performance of a metaheuristic and the quality of its solutions depend on its parameter values. However, finding a good parameter setting is a time-consuming task. In this work, we apply the upper confidence bound (UCB) algorithm to automate offline tuning in a (1 + 1)-evolution strategy. Preliminary results show that our proposed approach is a less costly method.
Smart edge segmentation and localization method for building detection in satellite imagery
Authors: Hashmi Hina , Dwivedi Rakesh , Kumar Anil , Kumar Aman
Published: April 2024

The rapid advancements in satellite imaging technology have brought about an unprecedented influx of high-resolution satellite imagery. One of the critical tasks in this domain is the automated detection of buildings within satellite imagery. Building detection holds substantial significance for urban planning, disaster management, environmental monitoring, and various other applications. The challenges in this field are manifold, including variations in building sizes, shapes, orientations, and surrounding environments. Furthermore, satellite imagery often contains occlusions, shadows, and other artifacts that can hinder accurate building detection. The proposed method introduces a novel approach to improve the boundary detection of detected buildings in high-resolution remote sensed images having shadows and irregular shapes. It aims to enhance the accuracy of building detection and classification. The proposed algorithm is compared with Customized Faster R-CNNs and Single-Shot Multibox Detectors to show the significance of the results. We have used different datasets for training and evaluating the algorithm. Experimental results show that SESLM for Building Detection in Satellite Imagery can detect 98.5% of false positives at a rate of 8.4%. In summary, SESLM showcases high accuracy and improved robustness in detecting buildings, particularly in the presence of shadows.
Methods and key issues of classroom behavior recognition for students based on artificial intelligence
Authors: Yang Wenyang , Li Mengdi
Published: April 2024

The development of computer vision and artificial intelligence provides technical support for objective evaluation of classroom teaching, and promotes the implementation of personalized teaching by teachers. In traditional classroom teaching, due to limitations, teachers are unable to timely understand and evaluate the effectiveness of classroom teaching through students’ classroom behavior, making it difficult to meet students’ personalized learning needs. Using artificial intelligence, big data and other digital technologies to analyze student classroom learning behavior is helpful to understand and evaluate students’ learning situation, thus improving the quality of classroom teaching. By using the method of literature analysis, the paper sorts out relevant domestic and foreign literature in the past five years, and systematically analyzes the methods of student classroom behavior recognition supported by deep learning. Firstly, the concepts and processes of student classroom behavior recognition are introduced and analyzed. Secondly, it elaborates on the representation methods of features, including image features, bone features, and multimodal fusion. Finally, the development trend of student classroom behavior recognition methods and the problems that need to be further solved are summarized and analyzed, which provides reference for future research on student classroom behavior recognition.
The phase transition in random regular exact (3s + s, k)-SAT problem
Authors: Tang Ao , Wang Xiaofeng , Peng Qingyuan , Wang Junxia , Yang Yi , He Fei , Hua Yingying
Published: April 2024

A CNF formula with each clause of length k and each variable occurring 4s times, where positive occurrences are 3s and negative occurrences are s, is a regular (3s + s, k)-CNF formula (F3s+s,k formula). The random regular exact (3s + s, k)-SAT problem is whether there exists a set of Boolean variable assignments such that exactly one literal is true for each clause in the F3s+s,k formula. By introducing a random instance generation model, the satisfiability phase transition of the solution is analyzed by using the first moment method, the second moment method, and the small subgraph conditioning method, which gives the phase transition point s* of the random regular exact (3s + s, k)-SAT problem for k≥3. When s < s*, F3s+s,k formula is satisfiable with high probability; when s > s*, F3s+s,k formula is unsatisfiable with high probability. Finally, through the experimental verification, the results show that the theoretical proofs are consistent with the experimental results.
A secure and scalable two-layer consensus algorithm based on PBFT
Authors: Huang De Ling , Huang Yi Fan , Yang Yu Qiao
Published: April 2024

Practical Byzantine Fault Tolerance (PBFT), the widest-used consensus algorithm in the alliance blockchain, suffers from high communications complexity and relatively low scalability, making it difficult to support large-scale networks. To overcome these limitations, we propose a secure and scalable consensus algorithm, Vague Sets-based Double Layer PBFT (VSDL-PBFT). Roles and tasks of consensus nodes are redesigned. Three-phase consensus process of the original PBFT is optimized. Through these approaches, the communication complexity of the algorithm is significantly reduced. In order to better fit the complexity of voting in the real world, we use a vague set to select primary nodes of consensus groups. This can greatly reduce the likelihood of malicious nodes being selected as the primary nodes. The experimental results show that the VSDL-PBFT consensus algorithm improves the system’s fault tolerance, it also achieves better performance in algorithm security, communications complexity, and transaction throughput compared to the baseline consensus algorithms.
Promoting quality career pathways for individuals with disabilities through the public vocational rehabilitation program
Authors: Chun Jina , Anderson Catherine. A , Rumrill Stuart , Richard Constance , Zhou Kaiqi , Fry Hannah , Froehlich Robert J.
Published: April 2024

BACKGROUND: Career Pathways initiatives in Vocational Rehabilitation (VR) have emerged as a crucial strategy for enhancing quality employment outcomes among individuals with disabilities. This paper conducts a comprehensive examination of the integration of Career Pathways within VR, emphasizing its significance in aligning vocational goals with evolving labor market demands. OBJECTIVE: Drawing from the innovative Career Pathways initiatives introduced by the Rehabilitation Services Administration (RSA), this paper addresses the RSA Career Pathways Demonstration Initiatives from 2015 to 2019 alongside the ongoing Disability Innovation Fund-Career Advancement Initiative Model Demonstration Project. The paper also discusses the strengthening of Career Pathways through the development of high-quality Individualized Plans for Employment and program evaluation. METHODS: This study utilized a modified exploratory case study approach to examine past and present career pathways initiatives in state VR agencies. Data were gathered from publicly available documentation and archival records, focusing on 12 cases from two national initiatives: the RSA Career Pathways Demonstration Initiatives (2015–2019) and the Disability Innovation Fund-Career Advancement Initiative Model Demonstration Project (2021–2026). RESULTS: The study reveals a substantial, positive impact on employment outcomes for individuals with disabilities through Career Pathways in VR programs, facilitated by the integration of adaptable pathways, individualized planning, and program evaluation.
Heart rate and oxygen saturation patterns in very low birth weight infants with early onset sepsis and histologic chorioamnionitis
Authors: Bultmann Charlene R. , Qiu Jiaxang , Belmonte Briana , Fairchild Karen D. , Sullivan Brynne A.
Published: April 2024

BACKGROUND:

Chorioamnionitis and early onset sepsis (EOS) in very low birth weight (VLBW,< 1500 g) infants may cause a systemic inflammatory response reflected in patterns of heart rate (HR) and oxygenation measured by pulse oximetry (SpO2). Identification of these patterns might inform decisions about duration of antibiotic therapy after birth.

OBJECTIVE:

Compare early HR and SpO2 patterns in VLBW infants with or without early onset sepsis (EOS) or histologic chorioamnionitis (HC).

STUDY DESIGN:

Retrospective study of placental pathology and HR and SpO2 in the first 72 h from birth in relation to EOS status for inborn VLBW NICU patients 2012–2019.

RESULT:

Among 362 VLBW infants with HR and SpO2 data available, clinical, or culture-positive EOS occurred in 91/362 (25%) and HC in 81/355 (22%). In univariate analysis, EOS was associated with higher mean HR, lower mean SpO2, and less negative skewness of HR in the first 3 days after birth. HC was associated with higher standard deviation and skewness of HR but no difference in SpO2. In multivariable modeling, significant risk factors for EOS were mean HR, gestational age, HC, mean SpO2, and skewness of SpO2.

CONCLUSION:

HR and SpO2 patterns differ shortly after birth in VLBW infants exposed to HC or with EOS, likely reflecting a systemic inflammatory response.
Experiences with mixed-mode surveys in times of COVID-19 at Statistics Netherlands
Authors: van Berkel Kees , van den Brakel Jan , Groffen Daniëlle , Burger Joep
Published: April 2024

Statistics Netherlands’ social surveys are based on a sequential mixed-mode data collection approach using web, telephone, and face-to-face interviewing. This article illustrates how Statistics Netherlands addressed the sudden, unforeseen loss of face-to-face interviews in social surveys amidst the COVID-19 pandemic. At the beginning of the pandemic, survey processes were immediately adjusted in several ways to mitigate the negative effects of respondent attrition. Where possible, sampled people initially assigned to face-to-face interviewing were motivated to respond through web or telephone to minimize the loss of response. At the same time regression analysis and simulation were conducted to obtain quantitative insight into the effects of losing face-to-face responses in the sequential mixed-mode designs. Furthermore, alternative model-based estimation procedures based on structural time series models were implemented to compensate for the bias that is a result of the loss of face-to-face responses. These initiatives are illustrated with applications to the Dutch Labor Force Survey, the Housing Survey, and the Health Survey.
Country statistical capacity: A recent assessment tool and further reflections on the way forward
Authors: Dang Hai-Anh H. , Jolliffe Dean , Serajuddin Umar , Stacy Brian
Published: April 2024

A country’s statistical capacity takes an indispensable part in its development. We offer a comprehensive comparison between the World Bank’s Statistical Performance Indicators and Index (SPI) and its predecessor, the Statistical Capacity Index (SCI) regarding different conceptual and empirical aspects. We further examine the relationships of the two indexes with some agriculture development indicators such as food security, food sustainability and productivity as well as other key indicators including headcount poverty, GDP per capita, and an SDG progress index. Our analysis employs the latest SPI data update in 2022, which were not available in previous studies. We also propose clear guidelines on how the SPI can be maintained and updated in the future to ensure that this process is transparent, replicable, safeguarded with high quality, and provides comparable data over time.
Enhancing taxonomy-based extraction: Leveraging information from online community platforms for digital skills demand identification in job ads
Authors: Napierała Joanna
Published: April 2024

The rapid technological changes have revolutionised how we function, including how we search for work and what skills we need to be equipped with to perform the tasks at the workplace. As employers more often recruit using online job advertisements, their content becomes a natural source of information for analytical purposes on the skills demanded in the labour market, especially for analysing emerging skills like digital. There are still some challenges with the extraction of information from online content. However, the extraction improvements go hand in hand with new technological developments like natural language processing techniques. This article presents the experimental method of updating the classification of digital skills to keep it up to date for information extraction applied to online job advertisements. The evaluation proved this method successfully identified terms related to programming skills but failed to identify terms associated with artificial intelligence sufficiently. The latter is related to the fact that the AI field is among the fastest developing areas of technology advancement, and new terms (e.g. Chatgpt) always appear.
Ensuring athlete physical fitness using Cyber-Physical Systems (CPS) in training environments
Authors: Zhou Hongtao , Daud D. Maryama Binti Ag
Published: April 2024

BACKGROUND: Sports have been a fundamental component of any culture and legacy for centuries. Athletes are widely regarded as a source of national pride, and their physical well-being is deemed to be of paramount significance. The attainment of optimal performance and injury prevention in athletes is contingent upon physical fitness. Technology integration has implemented Cyber-Physical Systems (CPS) to augment the athletic training milieu. OBJECTIVE: The present study introduces an approach for assessing athlete physical fitness in training environments: the Internet of Things (IoT) and CPS-based Physical Fitness Evaluation Method (IoT-CPS-PFEM). METHODS: The IoT-CPS-PFEM employs a range of IoT-connected sensors and devices to observe and assess the physical fitness of athletes. The proposed methodology gathers information on diverse fitness parameters, including heart rate, body temperature, and oxygen saturation. It employs machine learning algorithms to scrutinize and furnish feedback on the athlete’s physical fitness status. RESULTS: The simulation findings illustrate the efficacy of the proposed IoT-CPS-PFEM in identifying the physical fitness levels of athletes, with an average precision of 93%. The method under consideration aims to tackle the existing obstacles of conventional physical fitness assessment techniques, including imprecisions, time lags, and manual data-gathering requirements. The approach of IoT-CPS-PFEM provides the benefits of real-time monitoring, precision, and automation, thereby enhancing an athlete’s physical fitness and overall performance to a considerable extent. CONCLUSION: The research findings suggest that the implementation of IoT-CPS-PFEM can significantly impact the physical fitness of athletes and enhance the performance of the Indian sports industry in global competitions.
Tracking the Creativity of Autobiography and Biography Text Through Poster Media for Higher Education
Authors: Lubis Torkis , Arifin Zainul , Febriani Suci , Saputra Prayoga , Mela Desriliwa Ade , Bedra Kddour Geuttaoui
Published: April 2024

This research aims to analyze students' creativity in writing autobiography and biography texts in Arabic using poster media in higher education. Researchers used a qualitative approach with a case study method on 35 students. Data collection techniques used interviews, documentation and observation in Arabic writing skills learning activities, while the data analysis techniques used included triangulation of data sources identified through three stages, namely data collection, data reduction, data presentation and drawing conclusions. The research results show that: 1) Student creativity in writing autobiographical and biographical texts using posters is more varied with the choice of colors, images and identification of introductory texts, experiences and life learning; 2) the sentence structure used consists of five structures, namely the structure of verbs, nouns, adverbial attributes, properties and prepositions. Research findings show that the use of poster media in learning writing skills is able to develop creativity and a variety of sentence structures. This research is limited to only two texts, so the researcher recommends further research to analyze a variety of other texts using poster media and more varied research methods
BAURAN PEMASARAN AYAM BROILER DI PT BERKAH UTAMA SATWA KOTA BEKASI
Authors: Irma Puja Saputri  , Idah Yuniasih
Published: April 2024

ABSTRAK

Bauran pemasaran adalah kumpulan strategi pemasaran yang digunakan perusahaan untuk mencapai tujuan pemasaran tertentu. Penerapan bauran pemasaran dan saluran pemasaran yang terarah atau baik akan memudahkan perusahaan mencapai tujuan pemasarannya agar dapat bersaing dan menjangkau pasar yang lebih luas. Tujuan penelitian ini adalah untuk mengetahui bagaimana analisis bauran pemasaran ayam broiler pada PT Berkah Utama Satwa Kota Bekasi. Metode penelitian ini menggunakan penelitian deskriptif kualitatif dengan teknik pengumpulan data yang digunakan adalah teknik observasi, wawancara, dan dokumentasi. Hasil penelitian analisis bauran pemasaran ayam broiler PT Berkah Utama Satwa Kota Bekasi dapat dilihat dari bauran pemasaran ayam broiler dengan menggunakan 7P yaitu product, place, price, promotion, process, people, dan physical evidence. Kendala yang terjadi adalah pada saat mendistribusikan atau mengirimkan ayam, jarak antara perusahaan dan kandang cukup terlalu jauh yaitu dari Ciamis ke Bekasi sehingga pada saat pengiriman di perjalanan ada saja ayam yang sudah mati. Solusinya adalah perusahaan melakukan pengurangan dalam mengisi box pengiriman, yang awalnya berisi sekitar 20 ekor ayam menjadi 15 ekor ayam, supaya ayam yang didalam box selama perjalanan jauh tetap bisa bergerak sedikit bebas dan tidak mengalami kepanasan dan terakhir menyemprotkan air ke box ayam supaya mengurangi kepanasan saat diperjalanan.

Kata Kunci : Bauran Pemasaran, 7P

MARKETING MIX FOR BROILER CHICKENS

AT PT BERKAH UTAMA SATWA BEKASI CITY

 

ABSTRACT

Marketing mix is a collection of marketing strategy used by companies to achieve certain marketing objectives. The application of a targeted or good marketing mix and marketing channel will make it easier for companies to achieve their marketing objectives in order to compete and reach a wider market. The purpose of this study was to find out how the analysis of the broiler marketing mix at PT Berkah Utama Satwa in Bekasi City. This research method uses descriptive qualitative research with data collection techniques used are observation, interview, and documentation techniques. The results of the analysis of marketing mix analysis for broiler PT Berkah Utama Satwa in Bekasi City can be seen from the broiler marketing mix using 7Ps, namely product, place, price, promotion, process, people, and physical evidence. The obstacle that occurs is when distributing or sending chickens, the distance between the company and the coops is quite too far, namely from Ciamis to Bekasi so that when shipping is on the way there are dead chickens. The solution is for the company to reduce the filling in shipping boxes, which initially contained around 20 chickens to 15 chickens, so that the chickens in the box during long trips can still move a little freely and not experience overheating and finally spray water into the chicken box to reduce overheating while traveling.

Keyword : Marketing Mix, 7P
Customer Churn Prediction Using Machine Learning Algorithms
Authors: Shantanu Sonune  , Abhijeet Mohite  , Anjali Borhude  , Yash Patil  , Prof. Anuradha Thorat
Published: April 2024

In today’s highly competitive industries, retaining customers is vital for sustaining business growth and profitability. Customer churn, the phenomenon where customers switch from one service provider to another, poses a significant challenge for different companies. Predicting churn can help these companies take proactive measures to retain valuable customers. This study explores the application of machine learning algorithms for predicting customer churn in different industries like Telecom Industry, IT and Banking Sector. Additionally, the research contributes to the existing body of knowledge in the field of customer churn prediction, showcasing the potential of machine learning algorithms in addressing complex business challenges. The project begins with data collection and preprocessing, involving the extraction and cleaning of relevant features from diverse sources such as customer interactions, transaction history, and demographic information.The predictive modeling phase employs state-of-the-art machine learning algorithms, including but not limited to logistic regression, decision trees and random forest, feature engineering is employed to enhance the model's ability to capture nuanced customer behavior. The dataset is split into training and testing sets to evaluate model performance accurately.The outcomes of this project have practical implications for businesses aiming to proactively manage customer retention strategies. By identifying potential churners early, companies can implement targeted interventions, personalized marketing strategies, and loyalty programs to mitigate the risk of customer loss and foster long-term relationships.
Design And Implementation of Network Security Using Neural Network
Authors: Pankaj Sadhukhan  , Aniruddha Karmokar  , Arkodip Ganguly  , Soumya Paul
Published: April 2024

The number of internet users is increasing day by day. To keep internet surfing safe from vulnerable exploits we need to design new powerful algorithm. Hence this paper is mainly concerns with implementation of Neural Network using symmetric key cryptography to ensure confidentiality, authentication, integrity and message non-repudiation. In order to achieve the above objectives first an encryption algorithm is developed and implemented. The program takes a plain text as an input from the user to generate an intermediate cipher text and sends it to the source node of the neural network. At this point the intermediate cypher text is passed through some successive hidden layers of neural network’s concept to produce final cipher text. Now to recover the plain text from the final cipher text a decryption algorithm is developed and implemented.
As consequências da não declaração da inconstitucionalidade da confissão nos acordos de não persecução penal
Authors: Monteiro Bárbara Souza Silva , Demercian Pedro Henrique
Published: April 2024

O presente artigo analisou a constitucionalidade e relevância do requisito objetivo da confissão para a celebração do acordo de não persecução penal e demonstrou as consequências em razão da não declaração da inconstitucionalidade do dispositivo que prevê a obrigatoriedade da confissão. Além disso, demonstrou que a obrigatoriedade da confissão formal e circunstanciada vicia o acordo de não persecução penal por ausência da voluntariedade, uma vez que a confissão deve ser livre de qualquer pressão ou obrigação. Para tanto, utilizou-se o método indutivo com caráter expositivo, em que foi analisada a legislação vigente e as consequências em razão de algumas recomendações aos membros dos Ministérios Públicos do Brasil. Também foi apresentado um breve histórico acerca do acordo de não persecução penal, com a demonstração da evolução e o comparativo com o Direito Norte Americano, o qual baseou o acordo no ordenamento jurídico brasileiro. Verificou-se que a obrigatoriedade da confissão também fere a legislação internacional, incluindo a Convenção Americana de Direitos Humanos. Com isso, concluiu-se que a declaração da inconstitucionalidade do requisito objetivo da confissão para a celebração do acordo de não persecução penal é necessária, a fim de que haja segurança jurídica não só dos operadores do direito como também da população em geral.
Potensi Betanin Pada Analisis Logam Pb Dengan Metode Spektrofotometri UV-Vis
Authors: Kania Prina Puspa , Nursidika Perdina
Published: April 2024

Latar Belakang: Aplikasi zat warna alam yang terdapat di dalam sayur atau buah-buahan dalam analisis logam dapat digunakan dengan tujuan mengurangi perncemaran terhadap lingkungan. Betanin merupakan salah satu zat warna yang diketahui berpotensi sebagai zat pengompleks di dalam analisis logam dengan metode spektrofotometri UV-Vis. Potensi betanin sebagai zat pengompleks disebabkan karena keberadaan logam dapat mempengaruhi kestabilan warna betanin dan menyebabkan efek batokromik atau hipokromik. Tujuan: Penelitian ini bertujuan sebagai studi pendahuluan penggunaan betanin sebagai senyawa pengompleks dalam analisis logam Pb menggunakan metode Spektrofotometri Uv-Vis.. Metode: Penelitian ini dilakukan dengan mereaksikan antara larutan Betanin dengan larutan Standar Pb, kemudian kompleks yang terbentuk diukur serapannya menggunakan Spektrofotometri Uv-Vis pada Panjang gelombang maksimumnya. Hasil: Hasil penelitian diperoleh bahwa dengan berbagai variasi konsentrasi larutan standar Pb, absorbansi dari kompleks Betanin-Pb sesuai dengan Hukum Lambert-Beer dan diperoleh persamaan garis Y = 0,0066x + 0,5388 dengan R2-0,9991. Kesimpulan: Berdasarkan hasil penelitian yang diperoleh, diketahui bahwa Betanin dapat digunakan sebagai alternatif sebagai senyawa pengompleks pada analisis logam Pb dengan metode Spektrofotometri UV-Vis.
Efektivitas Penerapan Physical Distancing dalam Upaya Pengendalian Covid-19 di Kelurahan Siwalankerto
Authors: Marsela Arindis Pinky Ayu , Adriansyah Agus Aan
Published: April 2024

Latar Belakang: Penerapan physical distancing sering tidak dilakukan oleh masyarakat, sehingga pencapaian efektivitas physical distancing diperlukan sebagai upaya pengendalian Covid-19. Pengukuran efektivitas mengidentifikasi faktor physical distancing yang dilakukan oleh masyarakat. Tujuan: Penelitian ini bertujuan untuk menganalisis efektivitas penerapan physical distancing dalam upaya pengendalian Covid-19 di Kelurahan Siwalankerto. Metode: Penelitian ini merupakan penelitian kuantitatif dengan pendekatan desain deskriptif dengan pendekatan cross sectional. Populasi penelitian ini adalah 324 orang di Kelurahan Siwalankerto. Sampel ini yaitu kelompok rentan terkena Covid-19 yang dominan pada usia lansia (< 55 tahun). Besar Sampel yang digunakan sebanyak 116 orang dengan teknik cluster random sampling. Analisis data dengan univariat. Analisis mengukur program dengan rumus efektivitas. Hasil: Penelitian ini menunjukkan bahwa 7 indikator physical distancing pada durasi aktivitas di luar rumah (34,5%), batas aktivitas di luar rumah (48,3%), menjaga jarak (44,8%), bepergian (65,5%), berjabat tangan (73,3%), berdiam diri (69,8%), sentuh benda publik (86,2%). Kebijakan physical distancing ini cukup efektif jika dilakukan dalam pengendalian Covid-19. Kesimpulan: Penelitian ini menggambarkan bahwa tujuh kebijakan physical distancing yang cukup efektif dalam upaya pengendalian Covid-19, yang paling dekat efektif adalah menjaga jarak.
Faktor-Faktor Yang Berhubungan Dengan Kepatuhan Konsumsi Tablet Fe Pada Ibu Hamil Di Puskesmas Poasia
Authors: Liaumin Azim La Ode , Putri Dae Lestari , Misdayanti Misdayanti , Daranga Erniwati
Published: April 2024

Latar belakang: Salah satu masalah gizi yang banyak terjadi pada ibu hamil adalah anemia gizi. Salah satu upaya yang dapat dilakukan untuk mencegah aneia gizi adalah mengkonsumsi tablet Fe, namun masih banyak ibu hamil yang tidak patuh mengkonsumsi tablet Fe sampai 90 tablet. Puskesmas Poasia Kota Kendari, kepatuhan konsumsi tablet Fe Pada tahun 2020 hanya sebesar 88,6%. Tujuan: Penelitian ini bertujuan untuk mengetahui hubungan antara pendidikan, pengetahuan, dukungan suami dan pendapatan keluarga dengan Kepatuhan Konsumsi Tablet Fe Pada Ibu Hamil Trimester III di Wilayah Kerja Puskesmas Poasia Kota Kendari . Jenis penilitian yang digunanakan adalah observasional analitik dengan pendekatan Crosectional Study. Populasi dalam penelitian ini adalah Ibu Hamil Trimester III di Wilayah Kerja Puskesmas Poasia sebanyak 52 orang dan sampel yang digunakan sebesar 46 orang. Analisis data yang digunakan adalah chi square. Hasil: hasil penelitian menunjukan bahwa pendidikan (p-value = 0,033 ), pengetahuan (p-value = 0,029 ), dukungan suami (p-value = 0,029 ), pendapata keluarga (p-value = 0,412). Kesimpulan: pendidikan , pengetahuan dan dukungan suami berhubungan dengan Konsumsi Tablet Fe, sedangkan pendapatan keluarga tidak berhubungan dengan kepatuhan mengonsumsi tablet Fe pada ibu hamil trimester III di Wilayah Kerja Puskesmas Poasia Kota Kendari Tahun 2021
ПСИХОЛОГІЧНІ ОСОБЛИВОСТІ ВИРІШЕННЯ КОНФЛІКТІВ У ПРОФЕСІЙНІЙ ДІЯЛЬНОСТІ ПАТРУЛЬНОЇ ПОЛІЦІЇ
Authors: Андрусишин Роман Миколайович , Пряхіна Наталія Олексіївна
Published: April 2024

Суперечки та різного роду конфлікти у нашому суспільстві виступають як не дивно суспільним розвитком, супроводжуючи життя людей як невід’ємний його фактор. Конфлікт у роботі патрульної поліції можна вивчати або розглядати як зіткнення інтересів сторін, як мінімум однією з яких виступають працівники патрульної поліції. Можна наголосити, що у діяльності поліції або окремо у підрозділі можливі як внутрішньо-особистісні, міжособистісні конфлікти, конфлікти між особистістю і групою. Ну це можна назвати вертикальні (у відносинах субординації) або горизонтальні (поза відносин влади-підпорядкування) конфлікти, конфлікти всередині підрозділу поліції, між працівником поліцейського підрозділу і іншими особами (громадянином, установою), між працівниками поліцейського підрозділу. Визначено, що знати інформацію можливих причин виникнення, механізму розвитку і засобів попередження або ліквідації конфліктів дозволить визначити найбільш оптимальну лінію поведінки на шляху досягнення наміченої цілі в боротьбі з правопорушеннями. Виникнення якихось суперечок або конфліктів – одна із моментів або обставин, одна з невід’ємних характеристик службової діяльності працівника патрульної поліції. Поліцейський патрульної поліції може стати безпосереднім учасником суперечки чи конфлікту, при затриманні правопорушника або долаючи опір правопорушника, а також при вирішенні конфлікту чи суперечки між громадянами з метою його вирішення, протидія та попередження правопорушення тощо. Безпосередньо конфлікт або суперечка може виникнути в самому підрозділі поліції (між керівником i підлеглим, між працівниками різних служб). Проблема конфлікту в правоохоронній діяльності надзвичайно складна і багатоаспектна, тому ми розглянемо лише специфіку та особливості конфліктів, суб’єктом яких стає працівник при виконанні службових обов’язків. Обставина виникнення конфлікту з громадянами пояснюється лише тим, що з виконанням своїх професійних завдань на патрульного поліцейського покладаються різні обов’язки як адміністративно-правового, так і оперативно-розшукового характеру. Патрульна поліція є державною структурою, що має захищати громадян від злочинних та інших посягань, тому патрульні нерідко змушені застосовувати методи, які прямо або опосередковано обмежують передбачені законом права інших осіб. Всі ці моменти можуть призвести до загострення суперечки або конфлікту.
ПРАВА ЛЮДИНИ: ВТРУЧАННЯ У СФЕРУ ПРИВАТНОГО ЖИТТЯ В УМОВАХ ВОЄННОГО СТАНУ
Authors: Кучер Віталій Орестович
Published: April 2024

Дотримання права на приватність осіб під час воєнного стану є складною проблемою, оскільки військова агресія російської федерації потребує від держави здійснювати непопулярні заходи, які обмежують окремі права громадян для забезпечення безпеки та ефективності оборонних дій. Однак це не означає, що право на приватність повинно повністю ігноруватися. Втручання у сферу приватного життя особи без її згоди можливе лише тоді, коли це відбувається відповідно до вимог законодавства України та міжнародних правових норм; тільки в такому обсязі, в якому обмежувальні заходи будуть розмірними до переслідуваної мети відповідно до принципу пропорційності. Відомості про фізичну особу (персональні дані) є чутливою інформацією, а особливо в умовах воєнного стану. В Україні більшу увагу потрібно приділити інформаційній безпеці та системі захисту персональних даних, приведення її у відповідність до стандартів Європейського Союзу. Для забезпечення інформаційної, а як наслідок ˗ національної безпеки України, потрібно забезпечити захист важливих елементів персональних даних осіб шляхом створення міжгалузевої багатофункціональної інформаційної інфраструктури держави. Потребує вдосконалення рівень координації діяльності державних органів щодо виявлення, оцінки і прогнозування загроз інформаційній безпеці, запобігання таким загрозам та забезпечення ліквідації їх наслідків, здійснення міжнародного співробітництва з цих питань; вдосконалення нормативно-правової бази щодо забезпечення інформаційної безпеки, зокрема захисту інформаційних ресурсів, протидії комп’ютерній злочинності, захисту персональних даних, а також правоохоронної діяльності в інформаційній сфері. Як наслідок, необхідно удосконалювати форми організації, взаємодії, координації діяльності органів державної влади у напрямку забезпечення процесу управління загрозами та небезпеками в умовах воєнного стану.
ОСНОВНІ ІСТОРИЧНІ МЕТОДИКИ ІНТЕРПРИТАЦІЇ ПРАВА: ІУДЕЙСЬКА ТА РИМСЬКА ШКОЛИ
Authors: Кобко-Одарій Вікторія Сергіївна
Published: April 2024

Стаття присвячена дослідженню основних історичних методик тлумачення права. Зокрема, увага приділяється іудейській та римській історичним школам. Ця тема є досить актуальною в наш час, оскільки це питання є недостатньо розробленим у вітчизняній науці. Існує велика кількість робіт, в яких досліджуються сучасні методи тлумачення права, але дуже мало уваги приділяється вивченню історичних витоків тлумачення права. Вивчення цієї теми дозволить глибше дослідити феномен історичних способів тлумачення, проаналізувати причини їх виникнення та розвитку, а також збагатить юридичну науку новими ідеями та теоріями. Автором встановлено, що найбільший вплив на сучасну інтерпретацію права мала іудейська та римська думки. Тлумачення права в цих соціальних спільнотах було значною мірою зумовлене і пов'язане з сакральним началом, яке виробило власні методи тлумачення. Автор виведено припущення, що ці школи тлумачення права не є тотожними, вони стоять окремо і мають свої специфічні відмінності. Для більш детального аналізу порушених питань нами також наведено низку реальних прикладів та обставин із тогочасних джерел права, які слугують доказовою базою для кожного типу вищезазначених методик. На основі отриманих даних з'ясовано, що іудейське тлумачення права має більш теологічний характер і ґрунтується на релігійних текстах. А римське тлумачення права спочатку мало сакральний характер, але дуже швидко відійшло від своїх витоків і почало розвиватися іншим шляхом, а саме, віддаючи перевагу законам і тлумаченням видатних юристів того часу. Автор доходить висновку, що в сукупності вищезазначені історичні школи тлумачення права заклали підвалини власне тлумачення права і багато тисячоліть тому сформували методи тлумачення права, які й досі успішно застосовуються як в теорії, так і на практиці.
ОСОБЛИВОСТІ ПРОТИДІЇ ЗЛОЧИНАМ, ПОВ’ЯЗАНИМ З ТОРГІВЛЕЮ ЛЮДЬМИ, В УМОВАХ ВОЄННОГО СТАНУ
Authors: Рішко Василь Васильович
Published: April 2024

У статті розглянуто особливості протидії злочинам, пов’язаним з торгівлею людьми, в умовах воєнного стану. Для досягнення зазначеної мети використано діалектичний, статистичний, системно-структурний та формально-логічний методи. Підкреслено, що у ході російсько-української війни з’явилась нова група ризику – вимушені переселенці або внутрішньо переміщені особи із зони бойових дій. З початку вторгнення рф в Україну підрозділи міграційної поліції налагодили співпрацю з європейськими партнерами, зокрема Департаментом міграційної поліції під егідою Європолу спільно з правоохоронними органами країн Євросоюзу створено міжнародну інформаційну платформу в режимі 24/7. У рамках співпраці з європейськими поліцейськими проведені операції щодо протидії торгівлі дітьми, жебракуванню, сексуальній та трудовій експлуатації. У Нідерландах проведено день спільних дій EMPACT, який націлений на злочинні мережі, що використовують веб-сайти та платформи соціальних мереж для вербування жертв з метою сексуальної експлуатації. Зазначається, що спільні зусилля правоохоронних органів у моніторингу платформ, які можуть пропонувати сексуальні послуги, вербування та переховування чи транспортування жертв, сприяють боротьбі зі злочинами, пов’язаними з торгівлею людьми. Підкреслено, що важливе значення у підготовці працівників оперативних підрозділів Національної поліції до протидії злочинам, пов’язаним з торгівлею людьми, та іншим злочинам загальнокримінальної спрямованості набуває питання розвитку компетентностей працівників поліції для ефективного забезпечення їх професійної діяльності в умовах воєнного стану та післявоєнної відбудови економіки України. Набуття цих компетентностей можливе лише за умови отримання здобувачами вищої освіти знань, умінь та навичок під час навчального процесу у закладах вищої освіти та закріплення їх під час практики і стажування в практичних підрозділах Національної поліції.
How much is US Office Building Space Reduced per Teleworker?
Authors: Liu Kun , Guhathakurta Subhrajit , Han Chaeyeon , Hittinger Eric , Phoung Sinoun , Williams Eric
Published: April 2024

As office workers shift to telework, office building space requirements should decrease, but this relationship has not been empirically studied. We construct a dataset describing historical office building space, number of office workers, and number of teleworkers from 2003-2019 in the US, and use linear regression to estimate the effect of telework on office building space. The results show that the average office building space required for an additional office worker and teleworker is 32 and 18 square meters (340 and 191 square feet), respectively, suggesting an average 44% reduction in office building space when an office worker transitions to telework.