- Все статьи 611
Статьи журнала - International Journal of Information Engineering and Electronic Business
Все статьи: 611
Classification of the User's Intent Detection in E-commerce systems – Survey and Recommendations
Статья научная
The personalized experience gets more and more attention these days. Many e-commerce businesses are looking for methods to deliver personalized service. Consumers are expecting, if not demanding, highly personalized experiences. Moreover, customers are typically willing to spend more when they receive such a custom-tailored service. A prerequisite to provide a genuinely personalized experience is to understand the customer. Intent detection is a new and challenging approach in modern e-commerce to understand the customer. We find that various aspects of customer intent detection can be tackled by leveraging tremendous recent recommendation systems' progress. In this work, we review existing works from different domains that can be re-used for customer intent detection in the e-commerce. Even though many methods are used, there is no comparison of available approaches. Based on a review of nearly 100 articles from 2015 until 2019, we propose a categorization of types of intent detection, personalization context, building a customer profile, and dynamic changes in user interests handling. We also summarize existing methods from applicability in the e-commerce domain, including the aspect of the General Data Protection Regulation requirements. The paper aims at the classification of applied techniques and highlights their advantages and disadvantages.
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Classifying Similarity and Defect Fabric Textures based on GLCM and Binary Pattern Schemes
Статья научная
Textures are one of the basic features in visual searching,computational vision and also a general property of any surface having ambiguity. This paper presents a texture classification system which has high tolerance against illumination variation. A Gray Level Co-occurrence Matrix (GLCM) and binary pattern based automated similarity identification and defect detection model is presented. Different features are calculated from both GLCM and binary patterns (LBP, LLBP, and SLBP). Then a new rotation-invariant, scale invariant steerable decomposition filter is applied to filter the four orientation sub bands of the image. The experimental results are evaluated and a comparative analysis has been performed for the four different feature types. Finally the texture is classified by different classifiers (PNN, K-NN and SVM) and the classification performance of each classifier is compared. The experimental results have shown that the proposed method produces more accuracy and better classification accuracy over other methods.
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Client Server iOS in Player versus Player (PVP) of “Borneo Snap”
Статья научная
Borneo Snap is a Kalimantan’s animals snap card game. Play proceeds with the players taking it in turns to remove a card from the top of their deck and place it face-up on a central pile. If two cards placed consecutively on the pile are identical (same picture) then the first player to shout "Snap!"will get all of it. This game is built for the iOS platform. Game Player Versus Player (PVP) Borneo Snap using peer-to-peer API from Game Kit (XCode Framework) and Wi-Fi or Bluetooth, but actually, Borneo Snap uses client-server architecture model, each player in a player versus player game session only can communicate with server intermediaries. If the player sends data updates when playing cards to other players, this data update will first be through the server, then forwarded to all other players. The result of this research, with client-server framework Borneo Snap can be played by more than 1 player and more iOS gadget too
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Статья научная
The goal of the question-answering system is to respond to user queries expressed in natural language. Unlike search engines, the closed domain question answering systems are specialized to specific domains, providing concise and precise answers often derived from structured data. This paper focuses on a question-answering system tailored for crime events, capable of addressing both statistical and contextual inquiries. In terms of crime statistics, the fine-tuned GPT-3 model outperforms the USE, TAPAS, TAPEX, and GPT-3 models, while for context-based crime-related queries, the fine-tuned RoBERTa model surpasses the BERT and RoBERTa models. This system is capable of providing the responses in natural language format, supplemented with relevant data visualizations. The models are train on Q2A and NewsQA datasets while it is tested on NCRB and NewsTimes datasets. The Q2A and NCRB datasets are used for statistical queries while NewsQA and NewsTimes datasets are used for contextual inquiries. The paper presents an analysis of various models and showcases results for sample case studies. Such a system can prove valuable in applications where users seek to study criminal cases or gather pertinent insights for specific cases. Furthermore, it can assist in understanding patterns and trends in criminal events, particularly concerning geospatial information. Linking crime event-based question-answering systems to geospatial information facilitates exploration of niche areas and furnishes precise details about local crime with minimal hype and hence worth exploring.
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Cloud and On-premises Based Security Solution for Industrial IoT
Статья научная
In this paper, we take Industrial IoT (IloT) as a main point, where we touch on the direction of Industrial IoT concepts and connectivity protocols used by Industrial IoT devices. Moreover, we go into deep security challenges the Industrial ecosystem faces. Nowadays, most industries focus on specific protocols in their smart IoT devices. In return, we mainly focus on Message Queuing Telemetry Transport (MQTT) protocol, MQTT server where IoT devices are connected to it, and secure connectivity among server, cloud, and end user. Our purpose here is to describe the security approach for server and cloud-based environments and the utilization of cloud security tools such as IoT-hub, Network Security Group (NSG) and virtual private network (VPN). In more detail, here we have indicated proposed solution by separating into device, on-premises and cloud zone sections, proper technologies which are being used in modern security approaches and comparison with traditional IoT security approaches. This article enables readers to obtain fundamental knowledges on available technologies which are utilized in industrial areas and real-time scenarios where this solution is deployed.
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Статья научная
In this paper, we present the design and development of a collaborative knowledge-sharing platform with Blockchain based smart contracts (CodeBlockS) to help increase the trust and efficiency of how developers find the solution to their problems or try to learn new things. The popularity of Question-and-Answer websites such as StackOverflow, Ask, and Yahoo, as well as online course websites like as Udemy, is gradually expanding. Given this increased popularity, the quality and efficiency of user interaction must be improved such that users can try to connect with each other, ask questions about technical problems they are experiencing, or if they want to learn a topic in exchange for a fee and potentially collaborate on a project, or simply share their thoughts on a topic and improve their knowledge and network at the same time. Because these contracts will contain money, CodeBlockS has employed Ethereum Blockchain-based smart contracts to manage the data and money, as blockchain-based smart contracts are immutable and handle payments very securely. In general, social networking websites there are very few people sharing valuable knowledge and many people sharing worthless, time-consuming content that creates distraction. With the CodeBlockS system, developers find the solution to their problems or try to learn new things, and users can share their thoughts and learning on the platform. The platform also provides inbuilt smart contracts functionality using which two users can create a contract where one user will teach or solve doubt of the other user and receive fees towards service rendered.
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Coffee Leaf Disease Recognition Using Gist Feature
Статья научная
Coffee leaf disease recognition is important as its quality can be affected by the disease like –rust. This paper presents a coffee leaf disease recognition system with the help of gist feature. This research can help coffee producers in diagnosis of coffee plants in initial stage. Rocole coffee leaf dataset is considered in this study. Input image is pre-processed first. Resize and filtering is used as pre-processing work. Gist feature is extracted from pre-processed image. Extracted features are trained with machine learning algorithm. In testing phase, features are extracted and tested with trained ML model. Simulation is done with 10 fold cross validation. Different ML models are used and selected the best among them based on performance. SVM achieved overall 99.8% accuracy in recognizing coffee leaf disease.
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Color Histogram and DBC Co-Occurrence Matrix for Content Based Image Retrieval
Статья научная
This paper presents the integration of color histogram and DBC co-occurrence matrix for content based image retrieval. The exit DBC collect the directional edges which are calculated by applying the first-order derivatives in 0º, 45º, 90º and 135º directions. The feature vector length of DBC for a particular direction is 512 which are more for image retrieval. To avoid this problem, we collect the directional edges by excluding the center pixel and further applied the rotation invariant property. Further, we calculated the co-occurrence matrix to form the feature vector. Finally, the HSV color histogram and the DBC co-occurrence matrix are integrated to form the feature database. The retrieval results of the proposed method have been tested by conducting three experiments on Brodatz, MIT VisTex texture databases and Corel-1000 natural database. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP, DBC and other transform domain features.
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Common Fixed Point Theorem in Fuzzy Metric Spaces using weakly compatible maps
Статья научная
The aim of this paper is to prove a common fixed theorem for four mappings under weakly compatible condition in fuzzy metric space. While proving our results we utilize the idea of weakly compatible maps due to Jungck and Rhoades. Our results substantially generalize and improve a multitude of relevant common fixed point theorems of the existing literature in metric as well as fuzzy metric space.
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Статья научная
Knowledge processing is the prime area of information retrieval in the current era. However knowledge is subjected to the meaning of discretion in any natural language. Intelligent search in various Natural Languages is required in the huge repository of information available online. Language is the integral part for any form of communication but the language has to be meaningful. Semantics is a field of linguistics that deals with the meaning of the linguistic expressions through discovery of knowledge. In this research paper, the dictionary based approach for semantics is studied and implemented. The dictionary based proposal relies on the formalization of sentence across SVO (Subject-Verb-Object) format. Rule-based classifier helps to define the rules that are checked against the dictionary which contains sequence of Subject, Verbs and Object available in English Language. By looking at the accuracy measures, recall and precision the results obtained by the proposed approach is proven good.
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Comparative Advancements and Challenges of Branding Strategy in Business-to-Business Scenarios
Статья научная
Businesses have evolved with digitization and automation of manual processes through ERP solutions. These solutions fall under the category of being Business-To-Business (B2B) and help its clients to grow with a centralized solution to manage all business functions. It is easier for B2C companies to expand their reach using targeted branding strategies but takes a different approach for B2B companies to expand and grow as a Brand. It not only impacts how to reach a potential market but also impacts talent attraction and evolution into a trusted partner for potential market segments. Considering the case of an ERP company as large as SAP, various strategies are observed to target and attract potential customers as well as retain the existing clientele. This paper explores the concepts of Branding in a B2B scenario for an ERP company with a focus on SAP. It evaluates brand value, positioning, architecture, and expense comparison over the years and delves into a comparative study between SAP and one of its customers (B2C), Nestle, in terms of expenses and profits acquired. It also explores changes in Brand Strategy through Customer Advocacy, the importance of sales and marketing, and response strategies to the COVID-19 pandemic.
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Comparative Study of Website Page Size as Design Issue in Various Websites
Статья научная
Websites are very important means of communication in this current era of information technology. Different institutions / organizations put lots of efforts to portray complete information on beautifully designed websites. Organizations these days concerned more in providing users with all facilities online through websites, which act as an interface through which a user can get his work done without physically visiting the organization. With this the responsibility of the designer and the concerned institutions / organizations increases manifold so that the websites behavior should remain interactive and quick enough for the user to avail all facilities through websites comfortably. Speed and size of a Website are directly related with each other. Size is very important when targeting users that don't have optimal Internet connections. Author in this paper developed an online tool using .NET Framework using C# to study webpage size as Design issue in various categories of the websites like Government, Commercial, Educational, Social networking and Job portals. The automated tool developed by author function on the basis of the different standards prescribed in W3C and prescribed in analysis performed in [2]. The tool act like a parser and renders the complete code of the website and then produces result by examining the memory requirements of the component files that contribute to the total size of the website. The results produced shows that out of the five different categories of websites, it can be concluded that none of the website categories undertaken follows the recommended standards of the World Wide Web consortium showing huge violation as far as recommended page size for different websites is concerned.
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Comparative study of CEC’2013 problem using dual population genetic algorithm
Статья научная
Evolutionary Algorithms (EAs) are found to be effective for solving a large variety of optimization problems. In this Paper Dual Population Genetic Algorithm (DPGA) is used for solving the test functions of Congress on Evolutionary Computation 2013 (CEC’2013), by using two different crossovers. Dual Population Genetic Algorithm is found to be better in performance than traditional Genetic Algorithm. It is also able to solve the problem of premature convergence and diversity of the population in genetic algorithm. This paper proposes Dual Population Genetic Algorithm for solving the problem regarding unconstrained optimization. Dual Population Genetic Algorithm is used as meta-heuristic which is verified against 28 functions from Problem Definitions and Evaluation Criteria for the Congress on Evolutionary Computation 2013 on unconstrained set of benchmark functions using two different crossovers. The results of both the crossovers are compared with each other. The results of both the crossovers are also compared with the existing results of Standard Particle Swarm Optimization algorithm. The Experimental results showed that the algorithm found to be better for finding the solution of multimodal functions of the problem set.
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Comparison between Minutiae Based and Pattern Based Algorithm of Fingerprint Image
Статья научная
Fingerprint matching is the most accurate method among the biometrics. They are used for recognizing the person identity. The matching of two fingerprint images based on the numbering of minutiae and bifurcation points. Minutiae based Algorithm only extract local features of fingerprint image. The new algorithm used pattern based method which covers the whole area of fingerprint image. It includes both local and global features of fingerprint image. This new algorithm divides in three phases. First phase include enhancing the image quality with the thresholding value and reducing the dimensional space of fingerprint image with principal component analysis. Principal Component analysis contains the Principal components in lower dimensionality space with high value information. In second phase, Gabor filter is used for extracting feature vectors from fingerprint image and number of feature vectors form feature map. In third phase, Euclidean distance is calculated between two feature maps to determine whether the two fingerprint images are same or not. The result evaluation is done on the basis of bifurcation and minutiae points and their comparisons with previous work.
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Comparison of Two Methods Basing on Artificial Neural Network and SVM in Fault Diagnosis
Статья научная
Two diagnosis methods based on a neural network classifier and SVM are proposed for a pulse width modulation voltage source inverter. They are used to detect and identify the transistor open-circuit fault. BP neural network (BPNN) is capable of recognition. However, it has shortcomings obviously. These are just advantages of SVM, which has ability of global search. As an alternative to ANN, SVM can offer higher detection efficiency and reliability.
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Compromise Hypersphere for Multi-Criteria Dynamic Programming
Статья научная
The paper considers multi-criteria dynamic decision process. We focus on the efficient realizations of the dynamic process which are characterized by non-dominated values of the multi-period criteria function. The aim of the paper is to use the compromise hypersphere method to rank the efficient realizations. The presented method allows us to take into account the risk aversion of the decision maker. Moreover, we apply the presented theory in the market model taken from microeconomic theory.
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Computational Data Analysis on Global Energy and COVID-19 Pandemic
Статья научная
A global consumption of energy is primarily met by the renewable and non-renewable energy production resources. It is necessary to understand the pattern of global energy consumption in past to refine the overall energy policy for an upcoming demand of the energy market. The consumption of energy and its insights are helpful for grid management and forecasting. This paper presents the consumption of renewable and non-renewable energy resources by different nations and presents the analysis of the impact of COVID19 pandemic over the consumption of Energy. From the detailed analysis in this study, it is evident that all countries are shifting their interest to use renewable sources of energy generation. The global consumption of energy was constantly increasing up to 4% each year for three decades (1990 to 2020). However, during COVID-19 outbreak, energy consumption shows a downward trend in 2020 to -4%, which is twice lower than the decrement of energy consumption observed 2008-2009 economic crisis. The COVID-19 pandemic has seriously affected energy consumption of all countries in the world.
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Статья научная
This research solves the computational intelligence problem of devising two mathematical engineering tools called Classic-Curvature and Intensity-Curvature Functional. It is possible to calculate the two mathematical engineering tools from any model polynomial function which embeds the property of second-order differentiability. This work presents results obtained with bivariate and trivariate cubic Lagrange polynomials. The use of the Classic-Curvature and the Intensity-Curvature Functional can add complementary information in medical imaging, specifically in Magnetic Resonance Imaging (MRI) of the human brain.
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Conceptualization and Integration of Information Systems in Educational Business Activities
Статья научная
The business activities are highly incorporated with the technology development and need to be updated periodically. Business activities have made the technology to be more creative and innovative. The organizations need to integrate their business activities into a single system to achieve their aims and objectives successfully. Various studies are already conducted in integrating such business activities as Business Process Management System. In particular, various management systems are available in the market to integrate the educational business processes. The educational business processes are changing due to the various international bench markings. The educational business processes perspectives could not be met exactly to the requirements in some of the available software. As the currently available systems suits to some of the educational institutions in particular region of the world, there are needs to review them to the current requirements. This paper identifies the gaps between the current potential educational requirements and availability of educational business processes management systems. The major impact factors of the educational processes are identified and based on the findings a model has been proposed.
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Construction and Development of an Automated Greenhouse System Using Arduino Uno
Статья научная
An automated greenhouse is a framework that utilizes nursery innovations to make a positive ecological condition virtually to develop ideal creation of plants. Controlling climatic conditions are one of the most critical challenges in agribusiness. In like manner, a robotized nursery framework has been developed to accomplish observations and controlling of the climatic parameters which is straightforwardly or in a roundabout way that administers the plants development and generation. In a nursery using greenhouse structure that is made with glass or plastic it warms up from approaching obvious sun oriented radiation which is consumed by the plants and absorbed by the surface. Eventually air is warmed by the warmth from hot inside surfaces and held within the nursery dividers that makes the environment inside it warmer. With the association of present day innovations, this research takes a risk to actualize these frameworks for farming with no human consideration. The motivation behind this exploration is to make an innovation that makes exceedingly exact environment in a work sparing angle. In this work an Atmega328 MCU is utilized to do some predefined tasks, made by some specific codes with the help of an Arduino prototyping board. The system projects the parameters in a display as well as controls four vital parameters like temperature, light, humidity and soil moisture to accomplish viability and functionality of nursery environment control gadgets.
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