bluuebunny/crossref_metadata_2025 huggingface dataset:
LNG Opportunities for Harbor Development
Authors: Cok Loris  , De Zotti Luca  , Perosa Oscar
Published: February 2025

Today a “Green” vision of the Port becomes fundamental and LNG is more environmental friendly than any other fuel for its reduced emissions (nitrogen oxide, sulfur oxide and particulate matter). In the Mediterranean Sea, the environmental legislation has not yet imposed strict limits as it happened in the ECA / SECA zones. However, starting from 2020 or in any case by 2025, new regulations are planned to come into force. The distance of the LNG suppliers from the terminals and the LNG demand itself strongly affect the whole supply chain. One key point to consider for competitive planning and development of the LNG supply chain is that LNG carriers can supply connected harbors thus reducing the number of vessels involved and optimizing the quantity of LNG carried. The choice of using LNG as a fuel is growing because it reduces pollution and operative costs. The technology is ready to be used, but the port infrastructures have to face new challenges in the days to come. This study shows the possible scenarios (LNG supply system and pollution reduction) if using LNG in four different types of port.
Innovative Energy Systems: Motivations, Challenges and Possible Solutions in the Cruise Ship Arena
Authors: Boveri Alessandro  , Maggioncalda Matteo  , Rattazzi Diego  , Gualeni Paola  , Magistri Loredana  , Silvestro Federico  , Pietra Andrea
Published: February 2025

The worldwide effort on the environmental issue in the maritime field has led to always more stringent regulations on greenhouse gas emission (GHG). In this perspective, the International Maritime Organization has developed regulations intended to increase the ship's efficiency and reduce GHG emissions both in design phase, through the introduction of an Energy Efficiency Design Index (EEDI), either in management phase, adopting the Ship Energy Efficiency Management Plan (SEEMP). In this challenging perspective, several approaches and technologies adopted in land-based engineering can also be advantageous for marine applications. This is the case of the Distributed Energy Resources (DER) solution applied in land-based microgrids, which increases both the system's efficiency and reliability. This work is primarily focused on methodological aspects related to the adoption of a DER solution on-board cruise ships, with the integration of different energy sources in order to pursue a more flexible, reliable and sustainable management of the ship. In this context, another engineering best practice developed for land-based applications that is further investigated in the paper is related to the on board thermal energy recovery issue, revisited due to the implementation of the DER solution.
Experimental Investigation of Blade and Propeller Loads During Straight Ahead Sailing
Authors: Ortolani Fabrizio  , Dubbioso Giulio  , Santic Ivan  , Mauro Salvatore
Published: February 2025

During operative scenarios, the propeller can experience an inflow substantially different from the one considered in the design phases and the 3D character of the flow gives onset to a complete system of loads. The quantification of these loads is of paramount importance to assess the reliability of mechanical structures, the comfort on-board due to vibrations and the effects on the dynamic response of the vessel. In this work, a novel set up that allows to monitor the loads developed by a single blade was implemented on a free running, self propelled maneuvering model with the aim to investigate in details the performance of the propeller during realistic operative conditions. This preliminary work introduces the experimental set up and provides a preliminary overview of the results relative to straight ahead motion.
Monitoring Systems at the Service of Ship's Energy Efficiency: Measurements Campaign and Analysis of the Actual Electrical Absorptions on Board
Authors: Piastra Federica  , Qualich Stefano
Published: February 2025

The awareness of ship's energy efficiency is undeniably one of the top priorities of ship-owners, designers and operators; the aim is to comply the continuously updated regulations and to optimize the configuration of electrical machineries and their consumptions to reduce emissions and costs. Therefore also monitoring systems, historically connected to the ship structural condition, have been recently employed to assess the energy efficiency collecting information to improve it. In particular, one of the energetic monitoring branches is to monitor the actual electrical absorptions of on board consumers for a selected ship. In order to have impartial empirical information about operating absorption of consumers, a long-term measurements campaign have been organized and carried out with specific instrumentation based on ship's operating availability. The samples acquired during monitoring campaign have been combined with data from ship automation system, integrating the analysis with details of machineries concurrently operating (utilization and contemporary factors). This kind of analysis leads to results suitable for designers to benchmark the foreseen required electrical load on board: the subsequent possible impact on diesel generators' sizing and performance optimization and/or electrical system configuration, could lead to weights, volumes and cost efficiency.
Shore to Ship Power Supply Integrating Conventional and Distributed Generators Along with Storage
Authors: Torri Giordano  , Casini Silvio  , Piccin Andrea  , Mondo Denis
Published: February 2025

The need for reduction the pollution when ships are in port requires the use of a shore-to-ship power system for supplying energy to the onboard grid. The latter is normally fed at 60 Hz, so a frequency conversion is needed. Power can be taken from the public power grid available on shore. In order to reduce the environmental impact, this power system can be integrated with local, distributed generators that produce energy from renewable sources. Energy storage can also be added in order to smooth power peak demand and production from not programmable generators. The paper shows a system built around an Energy Box that manages the duty of all the power sources in parallel and provides the frequency conversion. A parallel on dc or ac side is considered, according to the power installed in a wide range from few MW up to 20 MW. The Energy Box is controlled by its own Power Management System in order to get a strong reduction of emissions, lower energy cost along with the best efficiency. An example of this technology is also shown.
An Italian Way for Yacht Coding?
Authors: Giunta Leonida
Published: February 2025

Many international conventions adopted at IMO level were conceived for “merchant” ships and their application to leisure yachts turned out to be challenging. That's why alternative solutions have been explored worldwide. In a nutshell, the idea was to create a set of rules and standards specifically adapted to this genre of vessel. Here, the key issue is represented by the establishment of technical, safety and operational parameters appropriate to the size and operation of the said crafts. A successful example of these attempts is offered by the two Codes of Practice published by the UK Maritime & Coastguard Agency (MCA): the Large Commercial Yacht Code (LY3) applicable to vessels of 24 metres and over in load line length that don't carry more than 12 passengers, and the Passenger Yacht Code (PYC) devoted to rule pleasure yachts of any size, which carry more than 12 but not more than 36 passengers. The Red Ensign Group (REG) is currently updating them through a new regulatory framework. Could this approach be followed also in Italy?
A Multilayer Intelligent System Architecture and Its Application to a Music Recommendation System
Authors: Sartori Fabio  , Melen Riccardo  , Redaelli Samuele
Published: February 2025

In this paper, we consider the problem of modeling application scenarios characterized by variability over time and involving heterogeneous kinds of knowledge. The evolution of distributed technologies creates new and challenging possibilities of creating innovative architectures that integrate different kinds of problem solving methods, obtaining many benefits from the user point of view. In particular, we propose here a multilayer modeling system and adopt the Wearable Expert System concept to tie together statistical and Artificial Intelligence rule-based methods. A music recommendation system applying this model has been implemented as a Cloud Mobile architecture.
How to Generate a Benchmark of Logical Argumentation Graphs?
Authors: Yun Bruno  , Croitoru Madalina  , Vesic Srdjan
Published: February 2025

In this demonstration extended abstract we present a workflow of how to generate a benchmark for logical argumentation graphs issued from knowledge bases expressed using existential rules.
Determining Classic Versus Modern Style in Fashion
Authors: Tauste Javier  , González Miguel Angel  , Museros Lledó  , Sanz Ismael  , Llidó Dolores  , González-Abril Luis
Published: February 2025

The role of the coolhunter (trendsetter) has gained importance in the fashion world. This role is in charge of detecting when new trends are occurring. Social media, with its blogs, forums, social platforms, etc., has made the information about clothes and trends more accessible. The task of filtering the relevant from the irrelevant is very difficult for the coolhunter, due to the avalanche of data and information produced in these media. Therefore, there is a need for an automatic system for detecting trends. Trends, or clothing style recognition, is a challenging problem due to wide variation in clothing item appearance, and even the subjectivity associate with the style concept. In fact, clothes that people wear contain latent fashion concepts capturing styles. Fashion theorists have proposed that these concepts are shaped by design elements such as color, material, and silhouette. While a dress may be “classic” because of its color, material, or some combination thereof, it is not always clear how low-level elements translate to high-level styles. This paper presents the firsts steps towards a system that helps in the task of trend determination. The paper presents a tool which has learnt to classify a style in a picture. Specifically, it is able to determine whether the clothes in an image represent a classic outfit or a modern outfit. This system is a cognitive system in the sense that it has been improved with data from a test designed to capture what people think it is classic or modern. We also provide the results of some experiments done using supervised machine learning techniques.
eXiT*CBR: A Tool Supporting RRI
Authors: López Beatriz  , Pous Carles
Published: February 2025

Researchers have the responsibility of guarantee the reproducibility of the experiments. To that end, open access policies are being implemented and adopted. But, in health sciences, openness finds its limitations with data privacy. Therefore, researchers need for alternative tools that support experiment repetition. In this paper we present eXiT*CBR which has been designed for this purpose, and we resume its use after 10 years.
Feature-Tree Labeling for Case Base Maintenance
Authors: Nakhjiri Nariman  , Salamó Maria  , Sànchez-Marrè Miquel
Published: February 2025

Case Base Maintenance (CBM) algorithms update the content of the case base with the aim of improving the case-based reasoner performance. In this paper, we introduce a novel CBM method called Feature-Tree Labeling (FTL) with the focus on increasing the general accuracy of a Case-Based Reasoning (CBR) system. The proposed FTL algorithm is designed to detect and remove noisy cases from the case base, based on value distribution of individual features in the available data. The competence of the FTL method has been compared with well-known state-of-the-art CBM algorithms. The tests have been done on 25 datasets selected from the UCI repository. The results show that FTL obtains higher accuracy than some of the state-of-the-art methods and CBR, with a statistically significant degree.
Including Hard Restrictions into Diet4You Menu Planner
Authors: Sevilla-Villanueva Beatriz  , Gibert Karina  , Sànchez-Marrè Miquel
Published: February 2025

Healthy life-styles have become a keystone of the modern health approach, according to its strategic role in preventing the development of some chronic diseases and maintaining the quality of life of persons. More and more, nutrition is central to guarantee a healthy life-style; following the proper diet is becoming essential from the health point of view. However, the current state of the art in nutrition is based on a design of diets made by nutritionists on the specific needs of each person, using their accumulated experience and some basic tools like tables of food decomposition. Well-formalized mechanisms supporting specific diet design are still limited. The project Diet4You proposes an intelligent decision support system oriented to the adaptive and dynamic preparation of personalized diets fitting nutritional prescriptions and adapted to specific health situation of a person, including genomics, personal habits and preferences or allergies. Diet4You is a hybrid system with a complex integration of artificial intelligence and analytic components, able to compose complete personalized menus, for a certain period of time. The Personal Menu Planner (PMP) is the specific component choosing the dishes to be proposed in the solution. In this work, a new component is developed to introduce possible restrictions specified by the nutritionist. There are many situations where the diet of a person is limited depending on his/her condition, allergies or personal decisions. Therefore, the new PMP obtains a menu that satisfies both the nutritional plan and the specified restrictions.
DECIMAXSUM: Using Decimation to Improve Max-Sum on Cyclic DCOPs
Authors: Cerquides Jesús  , Emonet Rémi  , Picard Gauthier  , Rodríguez-Aguilar Juan A.
Published: February 2025

When solving large distributed constraint optimization problems (DCOP), belief-propagation and incomplete inference algorithms are candidates of choice. However, these methods perform poorly when the factor graph is very loopy (i.e. cyclic) because of non-convergence and high communication costs. As to improving performances of the Max-Sum inference algorithm when solving loopy constraint optimization problems, we propose to take inspiration from the belief-propagation-guided decimation used to solve sparse random graphs (k-satisfiability). We introduce the DECIMAXSUM method, parameterized in terms of policies to decide when to trigger decimation, which variables to decimate, and which values to assign to decimated variables. Our empirical analysis on a classical BP benchmark indicates that some of these combinations of policies outperform state-of-the-art competitors.
Style Painting Classifier Based on Horn Clauses and Explanations (SHE)
Authors: Costa Vicent  , Dellunde Pilar  , Falomir Zoe
Published: February 2025

This paper presents an style painting classifier, based on Horn clauses in rational Pavelka logic and qualitative colour descriptors, that provides explanations (SHE). A fuzzy representation of colour traits for Baroque, Impressionism and Post-Impressionism art styles is introduced. The SHE-algorithm has been implemented in Swi-Prolog and tested on the 90 paintings in QArt-Dataset. the Baroque style was classified in 90% of accuracy. The general accuracy for all the art styles was 73.3%. SHE provided explanations of right classifications, and also of outliers by giving a second option depending on the membership degree of the painting to a certain style.
Retinal Optic Disc Segmentation Using Conditional Generative Adversarial Network
Authors: Singh Vivek Kumar  , Rashwan Hatem A.  , Akram Farhan  , Pandey Nidhi  , Sarker Md. Mostafa Kamal  , Saleh Adel  , Abdulwahab Saddam  , Maaroof Najlaa  , Barrena Jordina Torrents  , Romani Santiago  , Puig Domenec
Published: February 2025

This paper proposed a retinal image segmentation method based on conditional Generative Adversarial Network (cGAN) to segment optic disc. The proposed model consists of two successive networks: generator and discriminator. The generator learns to map information from the observing input (i.e., retinal fundus color image), to the output (i.e., binary mask). Then, the discriminator learns as a loss function to train this mapping by comparing the ground-truth and the predicted output with observing the input image as a condition. Experiments were performed on two publicly available dataset; DRISHTI GS1 and RIM-ONE. The proposed model outperformed state-of-the-art-methods by achieving around 0.96 and 0.98 of Jaccard and Dice coefficients, respectively. Moreover, an image segmentation is performed in less than a second on recent GPU.
Foreground Detection in a Multi-Target Fish Tracking from Video-Recordings Using U-Net Based Architecture
Authors: Reig-Bolano Ramon  , Serra I Serra Moises  , Marti-Puig Pere
Published: February 2025

One of the fundamental problems in computer vision is the background-foreground segmentation and most of the strategies have severe drawbacks when working with natural images, where there are extreme conditions such as illumination changes combined with sudden background differences or other noise; moreover if the system has to face real-time restrictions. In this case authors focus on a variation of the U-net architecture to obtain the segmentation of the objects (fishes) in every single frame. The U-net has some interesting properties to explore in the case of image segmentation, such as multi-scale parameter combination. The reported preliminary results, working in a context of a multi-target fish tracking are promising, and envisions an approach that could provide a real-time response to long-lasting experiments using HQ video for multi-target tracking in real-time Computer vision systems.
System Safety Analysis of an Industrial Process Using Fuzzy Methodology
Authors: Venditti Tony  , Tran Nguyen Duy Phuong  , Ngo Anh Dung
Published: February 2025

Industrial processes and machines pose risks in terms of equipment failure and worker accidents. In order to prevent these unwanted occurrences, the associated risks must first be analyzed. However, in traditional fault tree analysis, exact data values are used. But in real life often these values are not known precisely. There is therefore a degree of uncertainty associated with the data. Fuzzy numbers, expressed in this paper as triangular fuzzy number, provide a method for dealing and taking into account this uncertainty. In this paper, fuzzy fault tree analysis is then used. An example of a metal brake press is used to demonstrate this approach. A fault tree for a particular accident scenario is built and the fuzzy probability of occurrence of the accident under consideration is evaluated. An interesting second problem consists in starting with this value and deducing from the fault tree, what values of the occurrence probabilities of the contributing events in the fault tree minimize a function expressing the cost of work accidents. This problem is expressed mathematically and solved using a Matlab-based method over fuzzy numbers. The optimized contributing event probabilities are obtained along with the optimal cost function.
Implicational Tonoid Fuzzy Logics
Authors: Yang Eunsuk
Published: February 2025

This paper deals with one class of propositional fuzzy logics. Recently, fuzzy logic systems have been introduced as logics being complete with respect to linearly ordered algebras, in particular, algebras on the unit interval [0,1]. One of important trends in this logic is to introduce logic systems having more general structures. As one work of this trend, we introduce implicational tonoid fuzzy logics as fuzzy logics with tonic properties. For this, we first define implicational tonoid fuzzy logics in general. We then introduce their corresponding ternary relational semantics, called Routley–Meyer–style semantics. Routley–Meyer semantics was first introduced as semantics for relevance logics and then has been generalized to semantics for other non-classical logics. Finally, we prove that implicational tonoid fuzzy logics are sound and complete with respect to their corresponding Routley–Meyer–style semantics.
Regenerative Braking Force Allocation Control Strategy of Pure Electric Car Based on Multi-Objective Fuzzy Logic
Authors: Wang Xiaokan  , Yang Min  , Wang Qiong
Published: February 2025

The distribution method of regenerative braking force for pure electric car is studied. According to the speed and state of charge (SOC), a fuzzy logic based braking force distribution control strategy is proposed to achieve the better effective recovery of braking energy. The braking force distribution control strategy is simulated by MATLAB. The simulation results show that the energy recovery efficiency of regenerative braking is increased by 12.03%, and then the driving range of pure electric car is improved greatly.
Multimodal Sentiment Analysis Based on Feature Selection and Recurrent Neural Network
Authors: Xiao Zheng  , Zhang Huimin  , Wang Le  , Du Jiayi
Published: February 2025

Sentiment analysis is significant for social media. Although many achievements have been made, most of these are focused on either only text modality or only audio modality. In this paper, we proposed an architecture of multimodal sentiment analysis based on RNN and feature selection. It fully uses joint textual, audio and video features representation to perform multimodal sentiment analysis. By designing a feature selection component, we can select the informative features from the redundant and heterogeneous unimodal features to improve the performance of sentiment analysis model. At the same time, the additional RNN architecture can capture the dependency and information flow among the utterances of a video in a single modality and perform modality fusion at every timestep in the feature-level. The proposed method achieves better performance in sentiment prediction and shows improvement in performance over the baseline.
TNLCD: A Feasible Algorithm for Local Community Discovery in Temporal Networks
Authors: Chen Dongming  , Kong Lingya  , Wang Dongqi  , Huang Xinyu  , Fang Bo
Published: February 2025

Proposed a feasible algorithm for local community discovery in temporal networks named TNLCD. TNLCD algorithm is designed based on an improved temporal network model and a local modularity definition of our own for temporal networks. Experimental results on real-world datasets prove that TNLCD algorithm is not sensitive to initial nodes selection strategy and capable of revealing rich detailed community structure information which make the algorithm works well both in theoretical researches and practical applications.
A New Target Recognition Algorithm of Doppler Fuze Based on Extremum Points
Authors: Zhao Heming  , Xu Aiguo  , Jin Heli  , Wang Shen
Published: February 2025

According to the problems of the poor resistance to interference peak pulse arising from doppler fuze information processing circuit, which is composed of the analog devices, the paper raises the target signal extreme recognition algorithm and there are two kinds of target signal algorithm no interference and interference. In the method proposed herein, each point is compared with the average of the points in the front. Regarding signal amplitude and signal frequency, the efficiency is improved. The test results show that the target signal extreme recognition algorithm can completely remove the peak pulse interference part in the signal, and the method improves the anti-interference ability of doppler fuze and it has significant reference in the modern fuze digital transformation and improvement of the anti-interference ability.
The Application of Probability Risk Assessment Method in Space Robot Fine Operation
Authors: An Na  , Liu Shaohai  , Duan Yongsheng
Published: February 2025

In this paper, the probability risk assessment method and the probability risk assessment model are used to quantitatively analyze the security probabilities of space robots' target capture tasks. Based on the analysis of the process of capturing mission of the space robots, uncertainty analysis, importance degree and sensitivity results, objectively evaluate the weak link in the whole process of space robots target capture, and provide reference for the analysis of space robot in-orbit fault.
Line-of-Sight VLC in Inhomogeneous Underwater Medium: Performance Evaluation
Authors: Anous Noha  , Abdallah Mohamed  , Qaraqe Khalid
Published: February 2025

In this work, an underwater visible light communication vertical link is evaluated considering the inhomogeneity in underwater environment. The link is formed between an underwater transmitter (Tx) and a receiver (Rx) which is placed over a mount at the sea-level or above. Link budget formulas for the received power (Pr) are deduced. A numerical example is given to illustrate the BER performance under different link conditions. The effects of different system parameters such as average transmitted power (Pt), data rate (RB) and Tx orientation angle (θmin) on the BER performance are studied. When Ptincreases ten times, the maximum angular Rx position (θFEC) increases by 8%–14% for the same data rate. It is shown that maximum received power is obtained when the Tx is pointed upwards facing the sea-level. Moreover, the effect of Rx altitude from the sea-level is studied for different weather conditions. The provided results indicate that under heavy and moderate fog, the Rx is best located at the sea-level. Whereas under light foggy weather, two cases exist. If the average transmitted power is relatively low, the Rx is to be mounted above sea-level for better performance. However, if it is relatively high, the Rx is better placed at the sea-level.
Power Allocation Schemes for Distributed Antenna Systems (DAS) with Device-to-Device (D2D) Communication
Authors: Zhang Ce  , He Chunlong  , Li Xingquan  , Huang Lei
Published: February 2025

Many previous studies have mainly focused on resource allocation of distributed antenna systems (DAS) or device-to-device (D2D) communication of co-located antenna systems. In this paper, a new system model is considered for a coexistence scenario of DAS and D2D communications. Under the maximum transmit power constraint per antenna unit, we investigate two different optimization objectives for resource allocation. That is, maximum sum-rate (SR) and maximum energy efficiency (EE). Simulation results show that compared to DAS without D2D, the performance of the proposed system has a significant improvement in terms of SR and EE.
Analysis of Data from the Industrial Machinery Within the Hot Rolling Process for Predictive Maintenance
Authors: Ruiz-Sarmiento J.R.  , Monroy J.  , Moreno F.A.  , Bonelo J.M.  , Gonzalez-Jimenez J.
Published: February 2025

Manufacturing industries are increasingly adopting data-driven, decision making systems towards the Industry 4.0 paradigm. In the context of this data revolution, the innovative SiMoDiM project aims at developing a smart predictive maintenance system for the stainless steel industry. In its first stage, it focuses on the assets within the hot rolling process, one of the core components involved in the manufacturing of steel sheets, and more specifically on the coiler drums of Steckel mills. These drums operate under mechanical and thermal stresses that degrade them, and their replacements directly impact the product valor chain. In this work we present the data analysis stage of SiMoDiM, where the huge amount of available historical and real-time data from the hot rolling process (collected by onboard sensors in the mills) are studied in order to find which variables and descriptors are valid indicators of the coiler drums' conditions. This analysis is the first step towards an intelligent system that takes advantage of such descriptions for performing a predictive maintenance of the machinery.
Cognitive Incompatibilities Between Law and Robotic Legal-Decision Making
Authors: van Rompaey Léonard
Published: February 2025

This article examines the compatibility of law and robotics by comparing robotic and human legal-decision making. In a scenario where a robot and a person make exactly the same legal decision, with the same factual consequences, there would still be an important difference between the robotic and human decision-making processes. People will be able to relate to the human decision-maker, and this capacity shapes the judgment individuals have over the fairness of the decision and its outcome. Concurrently, individuals are not able to relate to the robot in the same scenario, and to reproduce the conditions of relatability in the robot is unforeseeable with the current development of cognitive sciences. Our capacity to judge the fairness or unfairness of the actions of others shapes our acceptance of and faith in the legal system. Robots making legal decisions would not recreate the same conditions of trust in the fairness of the legal-system, which is one source of incompatibilities between law and robotics.
On the Pertinence of Social Practices for Social Robotics
Authors: Clodic Aurélie  , Vazquez-Salceda Javier  , Dignum Frank  , Mascarenhas Samuel  , Dignum Virginia  , Augello Agnese  , Gentile Manuel  , Alami Rachid
Published: February 2025

In the area of consumer robots that need to have rich social interactions with humans, one of the challenges is the complexity of computing the appropriate interactions in a cognitive, social and physical context. We propose a novel approach for social robots based on the concept of Social Practices. By using social practices robots are able to be aware of their own social identities (given by the role in the social practice) and the identities of others and also be able to identify the different social contexts and the appropriate social interactions that go along with those contexts and identities.
Automatic Feature Extraction and Classification Model for Detecting Thai Clickbait Headlines Using Convolutional Neural Network
Authors: Kongyoung Sarawoot  , Rugchatjaroen Anocha  , Kaothanthong Natsuda
Published: February 2025

An automatic feature extraction for classifying the clickbait for Thai headlines is presented. The first corpus of 132,948 Thai headline news was collected. To transform Thai words into features, Word2Vec is utilized to overcome the ambiguity of the word segmentation. Then, the features are automatically extract using a Convolutional Neural Network (CNN). A number of experiments for CNN have been conducted to find the suitable value of the parameters that achieve the best classification result. We found that using a non-static modelling technique together with 50 dimension of Word2vec feature, {2, 3, 4} window size, and epoch equal to 5 achieves the accuracy of 95.25%. The experimental results also showed that the proposed method achieves the best result as compared to the other classification methods such as Support Vector Machine (SVM) and Naïve Bayes, which achieve 87.17% and 87.32%, respectively.
Semantic-Dependent Access Log Analysis for Predicting the Demographic Data
Authors: Matsumoto Kyohei  , Nakanishi Takafumi  , Kitagawa Takashi
Published: February 2025

We propose a new model, which is called the action-demographic interconnection model which realizes an interconnection function between customer actions and their customer demographic attribution. The features of our method are a semantic-dependent web access log analysis for predicting customer attribution. Our method makes predictions from a web access log. Therefore, we can determine what kind of customers are accessing each website. We present experiments for effectiveness with real advertising web access logs. Based on the results of the experiments, we discuss the possibility and the practicability of our proposed model.
A Chatbot Framework for the Children's Legal Centre
Authors: Morgan Jay  , Paiement Adeline  , Seisenberger Monika  , Williams Jane  , Wyner Adam
Published: February 2025

This paper presents a novel method to address legal rights for children through a chatbot framework by integrating machine learning, a dialogue graph, and information extraction. The method addresses a significant problem: we cannot presume that children have common knowledge about their rights or express themselves as an adult might. In our framework, a chatbot user begins a conversation, where based on the circumstance described, a neural network predicts both speech acts, relating to a dialogue graph, and legal types. Information is extracted in order to create a case for a legal advisor. In collaboration with the Children's Legal Centre Wales, who advocate for the improvement of legal rights in Wales, a corpus has been constructed and a prototype chatbot developed. The framework has been evaluated with classification measures and a user study.
Checking the Validity of Rule-Based Arguments Grounded in Cases: A Computational Approach
Authors: Zheng Heng  , Xiong Minghui  , Verheij Bart
Published: February 2025

One puzzle studied in AI & Law is how arguments, rules and cases are formally connected. Recently a formal theory was proposed formalizing how the validity of arguments based on rules can be grounded in cases. Three kinds of argument validity were distinguished: coherence, presumptive validity and conclusiveness. In this paper the theory is implemented in a Prolog program, used to evaluate a previously developed model of Dutch tort law. We also test the theory and its implementation with a new case study modeling Chinese copyright infringement law. In this way we illustrate that by the use of the implementation the process of modeling becomes more efficient and less error-prone.
Expressway Traffic Volume Prediction Using Floating Car Trajectory Data
Authors: Yuan Xianghong  , Yan Xiaoxiao  , Li Yang
Published: February 2025

As economy and construction rapidly grow, traffic problems become seri ous increasingly. To predict the traffic condition, it is particularly important to estimate the traffic volume. At present, GPS technology has good prospects in traffic information collection, vehicle guidance and so on. In this paper, a model is established based on vehicle information collected by GPS floating cars. The traffic volume is estimated by the number of vehicles between two floating cars. This method is easy to operate and has good real-time performance. The model is verified by comparing the estimated data with the measured data.
Influence of Calcium and Phosphorous Ratio on Hematology and Muscle Proximate Composition of Hypophthalmichthys molitrix Fingerlings
Authors: Arshad Mahnoor , Fatima Mahroze , Khizar Ayesha , Ishtiaq Haseeba , Ali Muhammad Adnan , Gulzar Muhammad Omer
Published: February 2025

Background. Calcium (Ca) and phosphorous (P) are essential minerals for fish growth and development, but Ca absorption from water is limited and its presence also influences P absorption. Therefore, dietary Ca and P are vital for fish to perform physiological activities efficiently.
Methodology.  This study investigated the interactive effect of Ca and P ratio (Ca:P) on muscle proximate composition and hematology of Hypophthalmichthys molitrix fingerlings (average initial weight = 13.7 ± 0.05 g) for 90 days. Calcium lactate and sodium di-phosphate were used as Ca and P sources. A total of 9 isonitrogenous, isolipidic, and isocaloric diets were formulated by combining 3 Ca levels (0%, 1%, and 2%) with three P levels (0%, 1%, and 2%) and fed to fish twice a day at 5% body weight.
Results. The results showed that moisture and crude protein content in muscles significantly increased (p<0.05) the interactive effect of Ca and P except fat and ash content (p>0.05). Furthermore, the hematological parameters of fingerlings remained unaffected (p>0.05) by the individual supplementation of Ca. However, P supplementation significantly affected the MCV, MHCH, and PLT count. Moreover, the interactive supplementation of Ca and P did not show a significant effect except HCT and MHCH. Platelets count increased at 1% of Ca and 1% of P supplementation, while the RBC count increased at 2% and 1 to 2% (Ca/P). The remaining blood counts did not show considerable variation upon supplementation of Ca/P at different levels.
Conclusion. It was concluded that mineral supplementation showed promising results at 1:2 (Ca/P) level for the optimum performance of H. molitrix.
Classical Biological Control of Brazilian Peppertree (Schinus terebinthifolia) in Florida
Authors: Cuda J.P. , Habeck D.H. , Overholt W.A. , Medal J.C. , Pedrosa-Macedo J.H. , Vitorino M.
Published: February 2025

This document discusses the classical biological control of the invasive Brazilian peppertree (Schinus terebinthifolia) in Florida. It highlights the tree’s aggressive spread, ecological impact, and the limitations of conventional control methods. The article details the introduction and effectiveness of various biological control agents, including thrips, sawflies, leaf rollers, weevils, and psyllids, in managing the Brazilian peppertree. The goal is to reduce the tree’s dominance and restore native biodiversity in affected ecosystems. First published 1999.
Pipevine Swallowtail, Blue Swallowtail Battus philenor (Linnaeus 1771) (Insecta: Lepidoptera: Papilionidae: Papilioninae: Troidini)
Authors: Hall Donald W.
Published: February 2025

This document provides an in-depth profile of the pipevine swallowtail butterfly, Battus philenor. It covers the butterfly’s nomenclature, distribution, physical description, life cycle, host plants, natural enemies, and defenses. The article also discusses the butterfly’s mimicry, pollination biology, and the ecological significance of its interactions with host plants and predators. The information is intended for both laypersons with some biological knowledge and academic audiences.
Integrated Pest Management at Home Series: Does your head itch? Facts About Head Lice
Authors: Nelson Nelly , Duncan LuAnn , Rodriguez Jenny , Allen Katherine , Stauderman Karen , Hamilton Lisa , Oi Faith
Published: February 2025

My head is itchy... could I have head lice? What are head lice? How do people get them? How do people inspect for them? How can people treat head lice? What should schools do about head lice? Will pesticides work? Will home remedies work? What can happen?!
Integrative Pest Management in the Home to the rescue!
The IPM at Home Series is a county faculty initiative intended to provide answers to frequently asked questions about household pests. This publication answers common questions about head lice. Aimed at the general public and delivered in a friendly, matter-of-fact style, it is intended to allay fears and provide practical help for people experiencing a common--and fortunately eminently solvable--problem.
ANALISIS FENOMENA MARITAL RAPE TERHADAP ANGKA PERCERAIAN PERSPEKTIF HUKUM ISLAM
Authors: Arifin Zaenal
Published: February 2025

Tujuan penulisan karya ini adalah untuk menganalisis fenomena marital rape mempengaruhi angka perceraian dan tinjauan hukum islam fenomena marital rape terhadap angka perceraian. Penelitian menggunakan metode tinjauan pustaka untuk menganalisis literatur tentang fenomena marital rape dan angka perceraian dari perspektif hukum Islam. Sumber data yang digunakan meliputi kitab-kitab hukum Islam, jurnal ilmiah, artikel, fatwa ulama, buku terkait, dan dokumen hukum terkini terkait kekerasan dalam rumah tangga dan marital rape. Teknik pengumpulan data dilakukan dengan mengidentifikasi dan memilih sumber-sumber literatur yang relevan. Data dianalisis dengan seksama untuk mengidentifikasi pandangan, fatwa, dan pendapat ulama, kemudian disintesis dan diorganisir untuk memberikan gambaran komprehensif tentang fenomena tersebut. Hasil karya ini yaitu a) Marital Rape menjadi faktor yang berpengaruh signifikan terhadap angka perceraian dalam masyarakat karena tindakan pemaksaan hubungan seksual dapat menyebabkan trauma dan cedera fisik pada istri, serta didukung oleh tayangan infotainment dan perubahan nilai-nilai sosial yang mempengaruhi persepsi terkait perkawinan dan perceraian. b) Tinjauan Hukum Islam terhadap fenomena Marital Rape menegaskan pentingnya mengedepankan prinsip kesetaraan, kasih sayang, dan izin dalam hubungan seksual antara suami dan istri untuk mengurangi angka perceraian dan menjaga keharmonisan dalam rumah tangga.
Exploring Organizational Motivation for Implementing Big Data Analytics: A Systematic Literature Review
Authors: Suroto Suroto
Published: February 2025

The objective of this study is to gain insights into the motivations behind organizations in adopting Big Data Analytics (BDA) by conducting a systematic literature review that provides the key determinants of BDA implementation in different sectors. This study follows the PRISMA guidelines using the PICOC principle to formulate research questions and establish inclusion criteria, and involves a systematic literature search followed by analysis to synthesize findings related to motivations for BDA adoption across sectors. The results of this study on the different sectors, including manufacturing, the public sector, Healthcare, education, and retail, have revealed that operational efficiency, product innovation, data management, and the management support of the organization act as the motivating factors in any BDA adoption decision. This study concludes that the motivation for BDA adoption across sectors is influenced by factors such as technological capabilities, organizational support, environmental pressures, and economic incentives, with specific differences in each sector indicating unique challenges and benefits, and offers a basis for further research and practical applications in the field of BDA.
Integrating K-Means Clustering and K-Nearest Neighbor Classification for Effective Scholarship Recipient Selection
Authors: Daulay Suandi , Wandri Rizky
Published: February 2025

This research is important because public interest in the KIP Kuliah Scholarship continues to increase. However, many educational institutions still use manual selection which is prone to bias and less effective in data management. Therefore, a method is required to make the selection process more efficient; the K-Means and K-Nearest Neighbor methods are two data processing methods that have been proven effective in various applications, including in the field of data processing. In this study, the K-Means and K-Nearest Neighbor methods are used to select scholarship recipients to increase efficiency in the process. Based on the processing carried out, there were 1257 participants who were then grouped into three clusters: Cluster 0 with 739 data points, Cluster 1 with 290 data points, and Cluster 2 with 228 data points. Testing using the K-Nearest Neighbor algorithm was carried out by evaluating the appropriate k values, specifically 27, 31, 35, 41, 45, and expanded to 185 to obtain the optimal value, namely K-155 and produced as many as 155 people who were deemed worthy and qualified according to the specified criteria. The combination of K-Means and K-NN algorithms resulted in an accuracy of 89.72% accomplished in 16 seconds. This combo can recognize data with excellent accuracy in a fast time while minimizing errors. The test results suggest that this technique is effective in selecting applicants based on the criteria and quotas established, thus it can be used as a guideline for future selection.
Integrated Tourism Development Strategy Model in Increasing Regional Revenue (PAD) and Community Economy in Southeast Sulawesi Province
Authors:   STIE Enam Enam Kendari, Nur Muh. , Barqi Sahbin ,   STIE Enam Enam Kendari, Budihard Andi M. ,   STIE Enam Enam Kendari, Asraf Asraf ,   STIE Enam Enam Kendari, Paluala Kusman ,   STIE Enam Enam Kendari
Published: February 2025

This study was conducted with the objectives of (1) identifying factors that influence the development of integrated tourism, (2) obtaining information on tourism destination management models to achieve tourism development that can increase Regional Income (PAD) and the community economy, and (3) obtaining information on strategies and concepts. The research locations were Bau-Bau City, North Konawe, Bombana, and Kolaka Regency. The analysis methods used were Partial Least Square (PLS) analysis and SWOT analysis. The results of this study are as follows: (1) Facilities and infrastructure in tourist areas currently only consist of several types. The existing facilities and infrastructure do not meet tourism quality standards due to a lack of attention from the local government; (2) The Tourism Office faces several challenges in developing the tourism sector. This is because tourism is not considered a primary or leading sector in these areas; (3) The development of the tourism sector cannot be separated from the progress of information technology, which is increasingly spreading in various regions in Southeast Sulawesi Province. The suggestion from the results of this study is that the Southeast Sulawesi government should hold/collect levies for each district that has tourist attractions to increase PAD
Understanding AI-Driven Threat Detection and Response Systems: A Technical Deep Dive
Authors: Deepak Gandham
Published: February 2025

This article presents a comprehensive analysis of artificial intelligence-driven threat detection and response systems in modern cybersecurity environments. The article examines the evolution of security infrastructure through the integration of advanced machine learning algorithms and automated response mechanisms. The article investigates the effectiveness of multi-tiered machine learning architectures in threat detection, behavioral analysis frameworks for user and device monitoring, and automated response capabilities. The article demonstrates significant improvements in detection accuracy, response times, and false positive reduction through AI optimization. The article indicates that the integration of quantum computing and advanced AI capabilities presents promising developments for future security systems, while maintaining operational efficiency and scalability across enterprise deployments.
The Significant Of Innovation and Its Imperative Part in Development, Survival and Success of Organizations
Authors: Dr. Swarooprani K
Published: February 2025

Innovation is one of the most significant concerns of each association and its role in the growth and coordination of the market is absolute. Innovation in all human areas is appropriate from creation development, methods of organization, ways of liability works and etc. In all of definition used for innovation, shifting or improvement of the method or product are common. Innovation is a procedure that begins with introduction to plan of an idea and will become a new purpose and so it different from creation. The major point is that novelty is different from originality. In this paper the significant of innovation and its vital role in growth, survival and winner of organizations is discussed.
A Review On: Exploration of Wild Edible Plants
Authors: Sanket P. Gawali  , Kulbhushan W. Pawar
Published: February 2025

Since the beginning of time, people have been gathering Wild Edible Plants (WEPs,) and they are now a staple of the human diet and conventional food systems. When food crops are few, WEPs continue to be crucial for maintaining food security and sovereignty, as well as having the potential to improve the well-being of non-significant households. The most popular Non-Timber Forest Products (NTFPs) are a Wild Edible Fruits (WEFs), which are also significant sources of revenue, medicine, and nourishment for those who use them. Besides being used as food, WEF species can produce fibre, fuel, and various processed goods. Farmers and breeders can cross them with domesticated crops to create new types because they have a variety of traits, such as drought tolerance and pest resistance. They contribute to enhancing the product's nutritional value and productivity. Furthermore, more research is needed to investigate the therapeutic potential and nutritional value of WEPs to provide a scientific foundation for further development of the herbal medicines and traditional foods, considering a above need review study was undertaken.