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Authors: YuLung Wu

Abstract:

In Knowledge Structure Graph, each course unit represents a phase of learning activities. Both learning portfolios and Knowledge Structure Graphs contain learning information of students and let teachers know which content are difficulties and fails. The study purposes "Dual Mode On-line Learning Diagnosis System" that integrates two search methods: learning portfolio and knowledge structure. Teachers can operate the proposed system and obtain the information of specific students without any computer science background. The teachers can find out failed students in advance and provide remedial learning resources.

Keywords: Knowledge Structure Graph, On-line LearningDiagnosis

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Authors: Vesile Evrim, Aliyu Awwal

Abstract:

By the evolvement in technology, the way of expressing opinions switched direction to the digital world. The domain of politics, as one of the hottest topics of opinion mining research, merged together with the behavior analysis for affiliation determination in texts, which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 were constituted by Linguistic Inquiry and Word Count (LIWC) features were tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that the “Decision Tree”, “Rule Induction” and “M5 Rule” classifiers when used with “SVM” and “IGR” feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “Function”, as an aggregate feature of the linguistic category, was found as the most differentiating feature among the 68 features with the accuracy of 81% in classifying articles either as Republican or Democrat.

Keywords: Politics, machine learning, feature selection, LIWC.

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Authors: Hassan Ezzaidi, Jean Rouat

Abstract:

Recently many research has been conducted to retrieve pertinent parameters and adequate models for automatic music genre classification. In this paper, two measures based upon information theory concepts are investigated for mapping the features space to decision space. A Gaussian Mixture Model (GMM) is used as a baseline and reference system. Various strategies are proposed for training and testing sessions with matched or mismatched conditions, long training and long testing, long training and short testing. For all experiments, the file sections used for testing are never been used during training. With matched conditions all examined measures yield the best and similar scores (almost 100%). With mismatched conditions, the proposed measures yield better scores than the GMM baseline system, especially for the short testing case. It is also observed that the average discrimination information measure is most appropriate for music category classifications and on the other hand the divergence measure is more suitable for music subcategory classifications.

Keywords: Audio feature, information measures, music genre.

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Authors: Mukesh Singh Boori, Venerando Eustáquio Amaro, Helenice Vital

Abstract:

The present study has been carried out with a view to calculate the coastal vulnerability index (CVI) to know the high and low sensitive areas and area of inundation due to future SLR. Both conventional and remotely sensed data were used and analyzed through the modelling technique. Out of the total study area, 8.26% is very high risk, 14.21% high, 9.36% medium, 22.46% low and 7.35% in the very low vulnerable category, due to costal components. Results of the inundation analysis indicate that 225.2 km² and 397 km² of the land area will be submerged by flooding at 1m and 10m inundation levels. The most severely affected sectors are expected to be the residential, industrial and recreational areas. As this coast is planned for future coastal developmental activities, measures such as industrializations, building regulation, urban growth planning and agriculture, development of an integrated coastal zone management, strict enforcement of the Coastal Regulation Zone (CRZ) Act, monitoring of impacts and further research in this regard are recommended for the study area.

Keywords: Coastal planning, land use, satellite data, vulnerability.

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Authors: Fendri Emna, Ben-Abdallah Hanêne, Ben-Hamadou Abdelmajid

Abstract:

In this paper, we present an approach for soccer video edition using a multimodal annotation. We propose to associate with each video sequence of a soccer match a textual document to be used for further exploitation like search, browsing and abstract edition. The textual document contains video meta data, match meta data, and match data. This document, generated automatically while the video is analyzed, segmented and classified, can be enriched semi automatically according to the user type and/or a specialized recommendation system.

Keywords: XML, Multimodal Annotation, recommendation system.

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Authors: Reza Ghaemi, Amin Milani Fard, Hamid Tabatabaee, Mahdi Sadeghizadeh

Abstract:

Due to new distributed database applications such as huge deductive database systems, the search complexity is constantly increasing and we need better algorithms to speedup traditional relational database queries. An optimal dynamic programming method for such high dimensional queries has the big disadvantage of its exponential order and thus we are interested in semi-optimal but faster approaches. In this work we present a multi-agent based mechanism to meet this demand and also compare the result with some commonly used query optimization algorithms.

Keywords: Information retrieval systems, list fusion methods, document score, multi-agent systems.

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Authors: Mohd Kamir Yusof, Suhailan Dato' Safei

Abstract:

Images are important in disease research, education, and clinical medicine. This paper presents a Web Service Platform (WSP) for support multiple programming languages to access image from biomedical databases. The main function WSP is to allow web users access image from biomedical databases. The WSP will receive web user-s queries. After that, it will send to Querying Server (QS) and the QS will search and retrieve data from biomedical databases. Finally, the information will display to the web users. Simple application is developed and tested for experiment purpose. Result from experiment indicated WSP can be used in biomedical environment.

Keywords: Biomedical, Image, Web Service Platform

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Authors: A. B. Dariane, A. M. Moradi

Abstract:

A direct search approach to determine optimal reservoir operating is proposed with ant colony optimization for continuous domains (ACOR). The model is applied to a system of single reservoir to determine the optimum releases during 42 years of monthly steps. A disadvantage of ant colony based methods and the ACOR in particular, refers to great amount of computer run time consumption. In this study a highly effective procedure for decreasing run time has been developed. The results are compared to those of a GA based model.

Keywords: Ant colony optimization, continuous, metaheuristics, reservoir, decreasing run time, genetic algorithm.

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Authors: N. Soussi, M. Bahaj

Abstract:

The enormous amount of information stored on the web increases from one day to the next, exposing the web currently faced with the inevitable difficulties of research pertinent information that users really want. The problem today is not limited to expanding the size of the information highways, but to design a system for intelligent search. The vast majority of this information is stored in relational databases, which in turn represent a backend for managing RDF data of the semantic web. This problem has motivated us to write this paper in order to establish an effective approach to support semantic transformation algorithm for SPARQL queries to SQL queries, more precisely SPARQL SELECT queries; by adopting this method, the relational database can be questioned easily with SPARQL queries maintaining the same performance.

Keywords: RDF, Semantic Web, SPARQL, SPARQL Query Transformation, SQL.

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Authors: H. Fabian Weber, Betina Szkudlarek

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The following study aims to outline, whether the perceptions of entrepreneurs about their entrepreneurial activities and the underlying meanings of their activities are universal or whether they vary systematically across cultures. In contrast to previous studies, the phenomenographical approach and the resulting findings of this study provide new insights into what constitutes entrepreneurship by drawing an inference from the perceptions of entrepreneurs in the United States and in Germany. Culture is shown to have an important impact on entrepreneurship, since the underlying meanings of entrepreneurship vary significantly among the two sample groups. Furthermore, the study sheds more light on the culturally contingent 'why' of entrepreneurship by looking at the internal motivations of individuals instead of exclusively focusing on character traits or external influences of the respective economic environments.

Keywords: Cross-Cultural Management, Entrepreneurship, Phenomenography, Qualitative Research.

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Authors: Aldrin R. Logdat, Marianne Christine Jane B. Capio

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The study aimed to investigate the impact of modelling techniques on the self-efficacy of first year Bachelor of Science Major in Hospitality Management (BSHM) college students at City College of Calapan, Oriental Mindoro. The research utilized a ten-point general self-efficacy scale and collected responses from a sample of 107 students across five BSHM sections. The study found that the majority of students had a moderate level of self-efficacy, with 49.53% of total respondents falling within this category. However, 35.51% of students had high self-efficacy, and 14.95% had low self-efficacy levels. The two-tailed t-test for independent samples indicated a significant difference between the mean post-test scores of the experimental and control groups. Furthermore, Wilcoxon test showed that there were significant differences in the experimental group's self-efficacy before and after treatment, while no such difference was observed in the control group. Thus, the modelling technique proved to be effective in improving the self-efficacy levels of first year BSHM college students. Ultimately, the use of modelling techniques helped to elevate students’ self-efficacy levels into higher categories.

Keywords: Self-efficacy, counselling, modelling techniques, hospitality management.

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Authors: F-E. Ouboutaib, A. Aitheda, S. Mekkaoui

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Marketing research is starting to focus on authenticity to position an offer, especially terroir products. However, with internet its usage remains more problematic. This paper investigates how digitalization impacts the satisfaction of the quest for authenticity. On the theoretical level, it explains authenticity in the online and offline context in the postmodernism era. Then, an exploratory qualitative study tries to understand the contribution of the digitization to the satisfaction of the search of authenticity. Therefore, cooperatives selling terroir product on the internet are advised to keep also direct contact which tends to show traditional manner of production, in order to enhance customers’ perception of terroir product authenticity.

Keywords: Authenticity, online authenticity, postmodernism, terroir products.

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Authors: Rein Kuusik, Grete Lind

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Generator of hypotheses is a new method for data mining. It makes possible to classify the source data automatically and produces a particular enumeration of patterns. Pattern is an expression (in a certain language) describing facts in a subset of facts. The goal is to describe the source data via patterns and/or IF...THEN rules. Used evaluation criteria are deterministic (not probabilistic). The search results are trees - form that is easy to comprehend and interpret. Generator of hypotheses uses very effective algorithm based on the theory of monotone systems (MS) named MONSA (MONotone System Algorithm).

Keywords: data mining, monotone systems, pattern, rule.

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Authors: P. Sengottuvelan, T. Gopalakrishnan

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Web Usage Mining is the application of data mining techniques to find usage patterns from web log data, so as to grasp required patterns and serve the requirements of Web-based applications. User’s expertise on the internet may be improved by minimizing user’s web access latency. This may be done by predicting the future search page earlier and the same may be prefetched and cached. Therefore, to enhance the standard of web services, it is needed topic to research the user web navigation behavior. Analysis of user’s web navigation behavior is achieved through modeling web navigation history. We propose this technique which cluster’s the user sessions, based on the K-medoids technique.

Keywords: Clustering, K-medoids, Recommendation, User Session, Web Usage Mining.

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Authors: Hanan A. M. Abd Alla, Lilac A. E. Al-Safadi

Abstract:

In this paper, a novel multi join algorithm to join multiple relations will be introduced. The novel algorithm is based on a hashed-based join algorithm of two relations to produce a double index. This is done by scanning the two relations once. But instead of moving the records into buckets, a double index will be built. This will eliminate the collision that can happen from a complete hash algorithm. The double index will be divided into join buckets of similar categories from the two relations. The algorithm then joins buckets with similar keys to produce joined buckets. This will lead at the end to a complete join index of the two relations. without actually joining the actual relations. The time complexity required to build the join index of two categories is Om log m where m is the size of each category. Totaling time complexity to O n log m for all buckets. The join index will be used to materialize the joined relation if required. Otherwise, it will be used along with other join indices of other relations to build a lattice to be used in multi-join operations with minimal I/O requirements. The lattice of the join indices can be fitted into the main memory to reduce time complexity of the multi join algorithm.

Keywords: Multi join, Relation, Lattice, Join indices.

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Authors: Chutimon Thitipornvanid, Siripun Sanguansintukul

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Choosing the right metadata is a critical, as good information (metadata) attached to an image will facilitate its visibility from a pile of other images. The image-s value is enhanced not only by the quality of attached metadata but also by the technique of the search. This study proposes a technique that is simple but efficient to predict a single human image from a website using the basic image data and the embedded metadata of the image-s content appearing on web pages. The result is very encouraging with the prediction accuracy of 95%. This technique may become a great assist to librarians, researchers and many others for automatically and efficiently identifying a set of human images out of a greater set of images.

Keywords: Metadata, Prediction, Multi-layer perceptron, Human facial image, Image mining.

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Authors: Yali Zheng, Peipei Luo, Shinan Chen, Jiasheng Hao, Hong Cheng

Abstract:

Most of traditional visual indoor navigation algorithms and methods only consider the localization in ordinary daytime, while we focus on the indoor re-localization in low light in the paper. As RGB images are degraded in low light, less discriminative infrared and depth image pairs are taken, as the input, by RGB-D cameras, the most similar candidates, as the output, are searched from databases which is built in the bag-of-word framework. Epipolar constraints can be used to relocalize the query infrared and depth image sequence. We evaluate our method in two datasets captured by Kinect2. The results demonstrate very promising re-localization results for indoor navigation system in low light environments.

Keywords: Indoor navigation, low light, RGB-D camera, vision based.

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Authors: N. Rugthaicharoencheep, T. Langtharthong

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This paper presents the optimal placement and sizing of distributed generation (DG) in a distribution system. The problem is to reliability improvement of distribution system with distributed generations. The technique employed to solve the minimization problem is based on a developed Tabu search algorithm and reliability worth analysis. The developed methodology is tested with a distribution system of Roy Billinton Test System (RBTS) bus 2. It can be seen from the case study that distributed generation can reduce the customer interruption cost and therefore improve the reliability of the system. It is expected that our proposed method will be utilized effectively for distribution system operator.

Keywords: Distributed generation Optimization technique Reliability improvement, Distribution system.

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Authors: Xing Li, Chengqing Zong

Abstract:

This paper presents an effective framework for Chinesesyntactic parsing, which includes two parts. The first one is a parsing framework, which is based on an improved bottom-up chart parsingalgorithm, and integrates the idea of the beam search strategy of N bestalgorithm and heuristic function of A* algorithm for pruning, then get multiple parsing trees. The second is a novel evaluation model, which integrates contextual and partial lexical information into traditional PCFG model and defines a new score function. Using this model, the tree with the highest score is found out as the best parsing tree. Finally,the contrasting experiment results are given. Keywords?syntactic parsing, PCFG, pruning, evaluation model.

Keywords: syntactic parsing, PCFG, pruning, evaluation model.

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Authors: T. Suresh Kumar, M. Arthanari, N. Shanthi

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Nowadays, the Web has become one of the most pervasive platforms for information change and retrieval. It collects the suitable and perfectly fitting information from websites that one requires. Data mining is the form of extracting data’s available in the internet. Web mining is one of the elements of data mining Technique, which relates to various research communities such as information recovery, folder managing system and simulated intellects. In this Paper we have discussed the concepts of Web mining. We contain generally focused on one of the categories of Web mining, specifically the Web Content Mining and its various farm duties. The mining tools are imperative to scanning the many images, text, and HTML documents and then, the result is used by the various search engines. We conclude by presenting a comparative table of these tools based on some pertinent criteria.

Keywords: Data Mining, Web Mining, Web Content Mining, Mining Tools, Information retrieval.

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Authors: Yasaswi Palagummi, Sareh Rowlands

Abstract:

Generalised Zero-Shot Learning, often known as GZSL, is an advanced variant of zero-shot learning in which the samples in the unseen category may be either seen or unseen. GZSL methods typically have a bias towards the seen classes because they learn a model to perform recognition for both the seen and unseen classes using data samples from the seen classes. This frequently leads to the misclassification of data from the unseen classes into the seen classes, making the task of GZSL more challenging. In this work, we propose an approach leveraging the Shifted Window based Self-Attention in the Swin Transformer (Swin-GZSL) to work in the inductive GZSL problem setting. We run experiments on three popular benchmark datasets: CUB, SUN, and AWA2, which are specifically used for ZSL and its other variants. The results show that our model based on Swin Transformer has achieved state-of-the-art harmonic mean for two datasets - AWA2 and SUN and near-state-of-the-art for the other dataset - CUB. More importantly, this technique has a linear computational complexity, which reduces training time significantly. We have also observed less bias than most of the existing GZSL models.

Keywords: Generalised Zero-shot Learning, Inductive Learning, Shifted-Window Attention, Swin Transformer, Vision Transformer.

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Authors: Meriem Benzarti, Mohamed Ben Tkaya, Cyril Pailler Mattei, Hassan Zahouani

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Hair is a non homogenous complex material which can be associated with a polymer. It is made up 95% of Keratin. Hair has a great social significance for human beings. In the High Middle Ages, for example, long hairs have been reserved for kings and nobles. Most common interest in hair is focused on hair growth, hair types and hair care, but hair is also an important biomaterial which can vary depending on ethnic origin or on age, hair colour for example can be a sign of ethnic ancestry or age (dark hair for Asiatic, blond hair for Caucasian and white hair for old people in general). In this context, different approaches have been conducted to determine the differences in mechanical properties and characterize the fracture topography at the surface of hair depending on its type and its age. A tensile testing machine was especially designed to achieve tensile tests on hair. This device is composed of a microdisplacement system and a force sensor whose peak load is limited to 3N. The curves and the values extracted from each experiment, allow us to compare the evolution of the mechanical properties from one hair to another. Observations with a Scanning Electron Microscope (SEM) and with an interferometer were made on different hairs. Thus, it is possible to access the cuticle state and the fracture topography for each category.

Keywords: Hair, relaxation test, SEM, interferometer, mechanical properties.

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Authors: Imran Ahmed, Muhammad Islam, Syed Inayat Ali Shah, Awais Adnan

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The identification and classification of weeds are of major technical and economical importance in the agricultural industry. To automate these activities, like in shape, color and texture, weed control system is feasible. The goal of this paper is to build a real-time, machine vision weed control system that can detect weed locations. In order to accomplish this objective, a real-time robotic system is developed to identify and locate outdoor plants using machine vision technology and pattern recognition. The algorithm is developed to classify images into broad and narrow class for real-time selective herbicide application. The developed algorithm has been tested on weeds at various locations, which have shown that the algorithm to be very effectiveness in weed identification. Further the results show a very reliable performance on weeds under varying field conditions. The analysis of the results shows over 90 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.

Keywords: Weed detection, Image Processing, real-timerecognition, Standard Deviation.

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Authors: Eric Filiol

Abstract:

This paper presents a protocol aiming at proving that an encryption system contains structural weaknesses without disclosing any information on those weaknesses. A verifier can check in a polynomial time that a given property of the cipher system output has been effectively realized. This property has been chosen by the prover in such a way that it cannot been achieved by known attacks or exhaustive search but only if the prover indeed knows some undisclosed weaknesses that may effectively endanger the cryptosystem security. This protocol has been denoted zero-knowledge-like proof of cryptanalysis. In this paper, we apply this protocol to the Bluetooth core encryption algorithm E0, used in many mobile environments and thus we suggest that its security can seriously be put into question.

Keywords: Bluetooth encryption, Bluetooth security, Bluetoothprotocol, Stream cipher, Zero-knowledge, Cryptanalysis

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Authors: Ali M. Alakeel

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Assertion-Based software testing has been shown to be a promising tool for generating test cases that reveal program faults. Because the number of assertions may be very large for industry-size programs, one of the main concerns to the applicability of assertion-based testing is the amount of search time required to explore a large number of assertions. This paper presents a new approach for assertions exploration during the process of Assertion- Based software testing. Our initial exterminations with the proposed approach show that the performance of Assertion-Based testing may be improved, therefore, making this approach more efficient when applied on programs with large number of assertions.

Keywords: Software testing, assertion-based testing, program assertions.

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Authors: Guruprasad Khataniar, Hitesh Tahbildar, Prakriti Prava Das

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There are various overlay structures that provide efficient and scalable solutions for point and range query in a peer-topeer network. Overlay structure based on m-Binary Search Tree (BST) is one such popular technique. It deals with the division of the tree into different key intervals and then assigning the key intervals to a BST. The popularity of the BST makes this overlay structure vulnerable to different kinds of attacks. Here we present four such possible attacks namely index poisoning attack, eclipse attack, pollution attack and syn flooding attack. The functionality of BST is affected by these attacks. We also provide different security techniques that can be applied against these attacks.

Keywords: BST, eclipse attack, index poisoning attack, pollution attack, syn flooding attack.

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Authors: Ebru Belkıs Kamanlıoğlu, Cem Güzeloğlu

Abstract:

As the new industrial revolution advances in the nanotechnology have been followed with interest throughout the world and also in Turkey. Media has an important role in conveying these advances to public, rising public awareness and creating attitudes related to nanotechnology. As well as representing how a subject is treated, media frames determine how public think about this subject. In literature definite frames related to nanoscience and nanotechnology such as process, regulation, conflict and risks were mentioned in studies focusing different countries. So how nanotechnology news is treated by which frames and in which news categories in Turkey as a one of developing countries? In this study examining different variables about nanotechnology that affect public attitudes such as category, frame, story tone, source in Turkish media via framing analysis developed in agenda setting studies was aimed. In the analysis data between 2005 and 2009 obtained from the first five national newspapers with wide circulation in Turkey will be used. In this study the direction of the media about nanotechnology, in which frames nanotechnologic advances brought to agenda were reported as news, and sectoral, legal, economic and social scenes reflected by these frames to public related to nanotechnology in Turkey were planned.

Keywords: Agenda, frames, media, nanotechnology, Turkey.

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Authors: Aikaterini Fountoulaki, Nikos Karacapilidis, Manolis Manatakis

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This paper proposes an innovative methodology for Acceptance Sampling by Variables, which is a particular category of Statistical Quality Control dealing with the assurance of products quality. Our contribution lies in the exploitation of machine learning techniques to address the complexity and remedy the drawbacks of existing approaches. More specifically, the proposed methodology exploits Artificial Neural Networks (ANNs) to aid decision making about the acceptance or rejection of an inspected sample. For any type of inspection, ANNs are trained by data from corresponding tables of a standard-s sampling plan schemes. Once trained, ANNs can give closed-form solutions for any acceptance quality level and sample size, thus leading to an automation of the reading of the sampling plan tables, without any need of compromise with the values of the specific standard chosen each time. The proposed methodology provides enough flexibility to quality control engineers during the inspection of their samples, allowing the consideration of specific needs, while it also reduces the time and the cost required for these inspections. Its applicability and advantages are demonstrated through two numerical examples.

Keywords: Acceptance Sampling, Neural Networks, Statistical Quality Control.

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Authors: N. Boudiaf

Abstract:

One major difficulty that faces developers of concurrent and distributed software is analysis for concurrency based faults like deadlocks. Petri nets are used extensively in the verification of correctness of concurrent programs. ECATNets are a category of algebraic Petri nets based on a sound combination of algebraic abstract types and high-level Petri nets. ECATNets have 'sound' and 'complete' semantics because of their integration in rewriting logic and its programming language Maude. Rewriting logic is considered as one of very powerful logics in terms of description, verification and programming of concurrent systems We proposed previously a method for translating Ada-95 tasking programs to ECATNets formalism (Ada-ECATNet) and we showed that ECATNets formalism provides a more compact translation for Ada programs compared to the other approaches based on simple Petri nets or Colored Petri nets. We showed also previously how the ECATNet formalism offers to Ada many validation and verification tools like simulation, Model Checking, accessibility analysis and static analysis. In this paper, we describe the implementation of our translation of the Ada programs into ECATNets.

Keywords: Ada tasking, Analysis, Automatic Translation, ECATNets, Maude, Rewriting Logic.

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Authors: Khashayar Jafari Kaliji

Abstract:

The paper aims to clarify the relationship between product involvement level and consumer tendency toward online review. It proposes the products in two classes and examines the level of user attention and significant difference between attribute-based areas and experience-based areas in each category. It uses an eye-tracking experiment to simulate the experience of online shopping behavior in order to view the consumers' shopping behavior. Thus, a scenario was designed, and 23 participants were asked step by step to purchase some products and add them to their shopping cart. The fixation durations are used to examine the amount of visual attention of the user in each area of interest (AOI) determined considering two classes of high involvement and low involvement products, and paired sample T-test was used to examine the effect of the product’s types on the online review content. The study results explained that users of high involvement products consider the attribute-based points more highly than the experience-based points.

Keywords: High-involvement products, low-involvement products, attribute-based review, experience-based review, eye tracking, fixation duration.

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