2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)最新文献_第6页

Sales Forecasting for Supply Chain Demand Management - A Novel Fuzzy Time Series Approach 面向供应链需求管理的销售预测——一种新的模糊时间序列方法

2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS) Pub Date : 2019-12-01 DOI: 10.1109/MACS48846.2019.9024810

S. Burney, S. Ali

{"title":"Sales Forecasting for Supply Chain Demand Management - A Novel Fuzzy Time Series Approach","authors":"S. Burney, S. Ali","doi":"10.1109/MACS48846.2019.9024810","DOIUrl":"https://doi.org/10.1109/MACS48846.2019.9024810","url":null,"abstract":"Supply chain management has become an important area of research among researchers in the past decade. The reason for its growing importance is its ability to enable businesses to have strategic competitive advantage. There are various supply chain functions and demand management is one of them. It deals with the organization's ability to meet the customer needs by maintaining the required inventory. In order to achieve this goal, organizations needs to predict the demand by forecasting sales using sales patterns in order to efficiently meet customer demands. Fuzzy time series has been extensively used for forecasting problems. The aim of this paper is to propose and implement a new fuzzy time series model to predict sales for efficient demand management within supply chain. This method was developed by us and previously used to predict university students' enrolment which had a better accuracy compared to existing methods. This paper will first discuss what sales forecasting and demand management is along with explaining the basics of fuzzy time series. Later the proposed framework will be discussed and applied to a sample monthly time series for milk cartons sales in a super market for sales forecasting. Later future research areas will be highlighted to conclude this research study.","PeriodicalId":434612,"journal":{"name":"2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133832956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Reciprocal Fit Concept in Mission Statement Research 使命宣言研究中的相互契合概念

2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS) Pub Date : 2019-12-01 DOI: 10.1109/MACS48846.2019.9024790

Seong-Yuen Toh, Jason Cheok, Sadia Ahmed Mughal

引用次数: 1

Sensor-less Control of a BLDC Motor for the Conversion of a Conventional Petrol Vehicle into a Solar-Electric Powered Vehicle 无传感器无刷直流电动机在传统汽油车转化为太阳能电动汽车中的控制

2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS) Pub Date : 2019-12-01 DOI: 10.1109/MACS48846.2019.9024775

Syed Saiq Hussain, M. A. Abbasi, Mehmood Ameer, Muhammad Kashif Majeed, Shahzad Karim Khawer, Muhammad Ahmed Khan

引用次数: 3

A mathematical Model for Selecting Features of Flooding Attacks Detection Methods based on Stability Criterion 基于稳定性准则的洪水攻击检测方法特征选择数学模型

2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS) Pub Date : 2019-12-01 DOI: 10.1109/MACS48846.2019.9024829

Abdulaziz Aborujilah, Nor Azlina Ali, R. Nassr, Mohd Nizam Husen, Abdulaleem Al- Othmani, K. A. Alezabi, Zalizah Awang Long

{"title":"A mathematical Model for Selecting Features of Flooding Attacks Detection Methods based on Stability Criterion","authors":"Abdulaziz Aborujilah, Nor Azlina Ali, R. Nassr, Mohd Nizam Husen, Abdulaleem Al- Othmani, K. A. Alezabi, Zalizah Awang Long","doi":"10.1109/MACS48846.2019.9024829","DOIUrl":"https://doi.org/10.1109/MACS48846.2019.9024829","url":null,"abstract":"In this era, the Internet represents the main tool of data searching and exchanging. By using Internet many apps in different locations, can be connected to each other remotely via web server connectivity. This connectivity is exposed to the internet vulnerabilities such as flooding attacks. Flooding attack is an example of an attack that causes harmful action against the web server resources or network bandwidth. Multivariate Correlation Analysis based Detection approach (MADM) is one of the statistical based detection (NIDS) approaches used to detect such attacks. However, MADM use predefined features that contain some intercorrelated features that have direct impact on classification performance. In this paper, a new extension on MADM architecture is proposed by adding SVM based feature selection method. So the mathematical formulation is explained. The proposed features selection method will be contributing in minimizing the false positive alarm rate and classification error rate.","PeriodicalId":434612,"journal":{"name":"2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130735133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cyber Security Issues and Challenges for Smart Cities: A survey 智慧城市的网络安全问题与挑战:调查

2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS) Pub Date : 2019-12-01 DOI: 10.1109/MACS48846.2019.9024768

Bushra Hamid, Noor Zaman Jhanjhi, M. Humayun, Azeem Khan, Ahmed Alsayat

{"title":"Cyber Security Issues and Challenges for Smart Cities: A survey","authors":"Bushra Hamid, Noor Zaman Jhanjhi, M. Humayun, Azeem Khan, Ahmed Alsayat","doi":"10.1109/MACS48846.2019.9024768","DOIUrl":"https://doi.org/10.1109/MACS48846.2019.9024768","url":null,"abstract":"The increasing need and implementation of Information Communication Technologies (ICT) in urban infrastructure have led to greater attention in smart cities. Smart cities make use of ICTs to enhance: the quality of life of citizens by paving the way to improve local economy, enhance transport system and transport management thereby providing conducive environment to build strong relationships together with public authorities. The assiduous goal of a smart cities is to improve the quality of life and services of citizens. Nevertheless, the instigation of ICTs has raised various issues pertaining to privacy and security issues concerned with smart cities and the inhabitants residing in them. The current research is an effort to present briefly the core concepts of security and privacy issues concerning to the smart cities and reveal cyber-attacks that were recent targeting smart cities based on current literature. Further, this research has elaborated and identified numerous security weaknesses and privacy challenges pertaining to various cyber security, the issues, challenges and recommendations in order to provide future directions.","PeriodicalId":434612,"journal":{"name":"2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)","volume":"66 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125849477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 42

Complex Network of Urdu Language 乌尔都语的复杂网络

2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS) Pub Date : 2019-12-01 DOI: 10.1109/MACS48846.2019.9024791

Nuzhat Khan, Muhammad Paend Bakht, Muhammad Junaid Khan, Abdul Samad

{"title":"Complex Network of Urdu Language","authors":"Nuzhat Khan, Muhammad Paend Bakht, Muhammad Junaid Khan, Abdul Samad","doi":"10.1109/MACS48846.2019.9024791","DOIUrl":"https://doi.org/10.1109/MACS48846.2019.9024791","url":null,"abstract":"This work proposes state of the art technique to examine composition patterns and topological structure of Urdu language. The improved method explores Urdu text in form of co-occurrence network graph within framework of complex network theory. For the first time, Urdu text is successfully transformed into graph despite having difficulties in dealing with Nastalik script, unavailability of resources and limited support by language processing tools. We have constructed an open and unannotated corpus of more than 3 million words using random forest approach. An un-directed, un-weighted graph from co-occurrence network of Urdu is created in python 3.4. Resulting network designed with bag of bigrams model consists of 5180 nodes and 101415 edges. Deep statistical analysis of graph is performed in graph visualization tool Gephi 0.9.2. Furthermore, a null model of similar size according to Erdos-Renyi random graph is generated to compare with Urdu network. Comparison is based on average path length, clustering coefficient and hierarchy of both networks. From analysis of these key features, it is observed that Urdu network graph differs from random network. Smaller average path length and high clustering coefficient also confirm small world effect in Urdu language. Additionally, 11 communities are detected in Urdu network unlike random network where only one community exists. Statistical facts reveal that Urdu network is a scale free network with layered composition pattern. Small world effect and scale free behavior of Urdu declare it a complex network with paradigmatic hierarchy in terms of authority distribution among words.","PeriodicalId":434612,"journal":{"name":"2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117084816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Automated UML-based Formal Model of E-Health System 基于uml的电子卫生系统形式化自动模型

2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS) Pub Date : 2019-12-01 DOI: 10.1109/MACS48846.2019.9024830

Marrium Khalid, Hamra Afzaal, Shoaib Hassan, N. Zafar, Saba Latif, Aniqa Rehman

{"title":"Automated UML-based Formal Model of E-Health System","authors":"Marrium Khalid, Hamra Afzaal, Shoaib Hassan, N. Zafar, Saba Latif, Aniqa Rehman","doi":"10.1109/MACS48846.2019.9024830","DOIUrl":"https://doi.org/10.1109/MACS48846.2019.9024830","url":null,"abstract":"The E-Health is a central part of monitoring and managing patient's health electronically at hospital. The existing patient treatment systems works manually because of ambiguities and limitations of semiformal techniques. Therefore, formal model of Patient Treatment System (PTS) as e-health is presented in this work with automation because it is difficult to provide correctness of a proposed model at modeling phase. In E-health system, the doctor scans the patient RFID tag for viewing and entering information in system, diagnosing, giving medicine and test prescription of patient. Further, doctor can view the current location of the patient through RFID number. Firstly, we have developed a semiformal model of the system using Unified Modeling Language (UML) because UML depicts better system design understandability. We have proposed an automated model using Non-Deterministic Automata (NFA) for describing system working in the form of states and transitions. Further, a formal model is developed in Vienna Development Method (VDM-SL) based on discrete mathematical concepts. Formal methods are used in this work to confirm robustness, accuracy and efficiency of the E-health system. The developed formal model is verified by VDM-SL toolbox. Further the maintenance and testing cost is reduced using automata and RFID based E-health system.","PeriodicalId":434612,"journal":{"name":"2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)","volume":"321 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133895029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Diabetic Retinopathy Detection based on Hybrid Feature Extraction and SVM 基于混合特征提取和支持向量机的糖尿病视网膜病变检测

2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS) Pub Date : 2019-12-01 DOI: 10.1109/MACS48846.2019.9024812

Tahira Nazir, A. Javed, Momina Masood, Junaid Rashid, Samira Kanwal

{"title":"Diabetic Retinopathy Detection based on Hybrid Feature Extraction and SVM","authors":"Tahira Nazir, A. Javed, Momina Masood, Junaid Rashid, Samira Kanwal","doi":"10.1109/MACS48846.2019.9024812","DOIUrl":"https://doi.org/10.1109/MACS48846.2019.9024812","url":null,"abstract":"Diabetes is a disease caused by high blood sugar levels in the body. Diabetic retinopathy (DR) is a vision-threatening disease that primarily affects people who have diabetes for many years. It is the major cause of blindness in people with diabetes. Medical work in this domain indicated that blindness could be prevented by providing proper treatment by diagnosing DR at the initial stage. The proper screening requires the training of manual graders to understand the type of DR. However, the overall cost of this screening program increases due to the complexity of this process and workload on pathologists. State of the art methods has focused on simple retinal image analysis to eliminate the patients who are not affected by this disease. Therefore, reducing the overall cost of this process by decreasing the workload of pathologists. The focus of this research work is to automatically detect the severity level of DR instead of just providing information about its presence that can further reduce the DR costs. Therefore, we designed an automated framework to extract the anatomy independent features and trained the SVM classifier to detect different DR stages. We used the Kaggle DR-data set to evaluate the performance of the proposed method. For each stage of DR, which indicates the effectiveness of the proposed technique, an average accuracy of 96.4% was achieved. Experimental results show that the proposed method can efficiently and reliably detect DR in large image data sets. The main contribution of the proposed work is to design efficient, cost-effective and fully automatic DR screening techniques.","PeriodicalId":434612,"journal":{"name":"2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115810644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

SAM: a Similarity Measure for Link Prediction in Social Network SAM:社交网络中链接预测的相似性度量

2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS) Pub Date : 2019-12-01 DOI: 10.1109/MACS48846.2019.9024762

A. Samad, Mamoona Qadir, Ishrat Nawaz

{"title":"SAM: a Similarity Measure for Link Prediction in Social Network","authors":"A. Samad, Mamoona Qadir, Ishrat Nawaz","doi":"10.1109/MACS48846.2019.9024762","DOIUrl":"https://doi.org/10.1109/MACS48846.2019.9024762","url":null,"abstract":"Research in the field of social network analysis attracting majority of the researchers nowadays. Out of many social network analysis problems, link prediction gaining high attention due to a growing number of social network users. Link prediction is a task to predict which new interaction is going to be occurring in the future. Traditional link prediction techniques considered pair of node as one unit and make decisions based on the commonality between them. We argued that both nodes in a pair have their own similarity to each other. It may be that one person is 100% similar to another, but the other person is not the same as the first. Moreover, we have proposed a similarity measure SAM for link prediction in the social network. We have compared SAM similarity with four other state-of-the-art link prediction techniques (i.e., Jaccard, Salton Index, Salton Cosine and Resource Allocation). The experiments in this paper are performed on five different datasets (i.e., Astro, CondMat, GrQc, HepPh and HepTh). Our results show that SAM performs better than rest of the link prediction techniques on all datasets.","PeriodicalId":434612,"journal":{"name":"2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124714062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Proposing a Rank and Wormhole Attack Detection Framework using Machine Learning 提出一种基于机器学习的秩和虫洞攻击检测框架

2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS) Pub Date : 2019-12-01 DOI: 10.1109/MACS48846.2019.9024821

Fatima-tuz-Zahra, Noor Zaman Jhanjhi, S. Brohi, Nazir A. Malik

{"title":"Proposing a Rank and Wormhole Attack Detection Framework using Machine Learning","authors":"Fatima-tuz-Zahra, Noor Zaman Jhanjhi, S. Brohi, Nazir A. Malik","doi":"10.1109/MACS48846.2019.9024821","DOIUrl":"https://doi.org/10.1109/MACS48846.2019.9024821","url":null,"abstract":"Internet of Things (IoT) is a paradigm in digital technology which is prevalently revolutionizing various sectors like healthcare, military, business and more. However, the incremental deployment of this advanced technology has also caused critical security issues simultaneously. In particular, IoT networks are continuing to grow vulnerable to security attacks due to exponential connectivity of ‘things’ with each other in the smart infrastructure. Due to this increased vulnerability, it has become crucial to address the issue of insecure routing in these IoT devices. IoT uses RPL, which is a specially designed standard for networking that caters to the resource-constrained and lightweight nature of IoT devices, for information broadcast. It is equally prone to routing attacks like any other class of protocols in wireless networks. Various solutions have been proposed by researchers to counter them including version, rank, sinkhole and wormhole attacks since last decade. However, given the huge impact, neither detection nor mitigation method has been found which addresses rank and wormhole attacks when they are initiated at the same time on an IoT network. In this paper, a rank and wormhole attack detection framework is proposed, by employing machine learning approaches, which address the stated issue. This research aims to contribute toward design and development of high-performing and effective solutions for routing attacks in RPL-based IoT networks.","PeriodicalId":434612,"journal":{"name":"2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122041737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 35