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检索条件"丛书名=Learning and Analytics in Intelligent Systems"

共 229 条记录，以下是141-150 订阅

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Complex Event Processing Based Analysis of Cassini–Huygens Interplanetary Dataset 1

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作者： AlDabbas, Ashraf Gál, Zoltán Faculty of Informatics University of Debrecen Debrecen4028 Hungary

ISBN: (数字)9783030385019

ISBN: (纸本)9783030385002;9783030385033

A complex event is an assortment of data observations that chimed to captivating of remarkable patterns in the implicit incident that are captured via the sensing devices. An innovative method is introduced in this research for the purpose of detecting complex events by analysing a huge dataset of images and other metadata that have been collected using remote sensing approach in Cassini–Huygens mission interplanetary expedition. The proposed method is competent to explore a big volume of data that is influenced by the indexed time-series manner using score array and the variation score of the target time intervals via the Weighted Complex Event Level (WCEL), allowing to convert the sensed data and images into spectacular detected events. It has been tested by applying it on all the batches which forming the included dataset and the results showed that almost in every batch there was more than a single complex event, within the 5 analysed phases of the mission, which include: Approach science phase, Extended phase, Extended-Extended phase, Tour, and Tour pre-Huygens phase. © 2020, Springer Nature Switzerland AG.

关键词： Big data

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Cyber Crime Investigation and Law 1

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作者： Chandrakala, N.B. Department of Law SPMVV AP Tirupati India

ISBN: (数字)9783030469399

ISBN: (纸本)9783030469382;9783030469412

Today we are living in the era of information technology where most of the activities of the private and public are dealt with the online transactions with the help of World Wide Web (www.) Anybody can access another via internet through online transaction. The entire world has become one global village. The people are connected closely with the help of internet and intranet. The internet has both uses and misuses. It is unfortunate to note that the internet is being misused by some of the criminals who use the hacking methods and blackmail the World Wide Web organisers and internet protocol users. Such criminals resort to the cyber crimes that use unauthorised access to the other’s networks. Such criminal activities come under the concept of cyber crimes [1]. At this juncture the ‘Cyber Law’ comes to the rescue of the aggrieved. Hence, the Cyber Law was introduced in the Indian legal domain. Cyber Law deals with the crimes through internet, cyberspace and addresses the computer related legal issues and corresponding punishments. Cyber Law also addresses the sub themes such as freedom of expression, access and utilization of internet, security via online including privacy. To put it in a short way it is termed a ‘the Law of the Web’ [2]. © 2020, Springer Nature Switzerland AG.

关键词： Cybersecurity

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Supporting System for Visiting Sightseeing Spot Using Image Recognition and Processing Technology (KadaBingo) 1

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作者： Ishikawa, Soma Izumi, Ryosuke Asakimori, Hiroki Yamada, Satoru Kunieda, Takayuki Kometani, Yusuke Gotoda, Naka Yaegashi, Rihito Graduate School of Engineering Kagawa University Hayashi-cho 2217-20 Kagawa Takamatsu761-0396 Japan Ricoh Inc. Nakamagome 1-3-6 Ota-ku Tokyo143-8555 Japan Faculty of Engineering Kagawa University Hayashi-cho 2217-20 Kagawa Takamatsu761-0396 Japan

ISBN: (数字)9783030539498

ISBN: (纸本)9783030539481;9783030539511

Utilization of gamification is increasing in the sightseeing filed. Gamification is all activities that uses game design techniques and mechanisms to solve issues and increase customer loyalty. It has been reported that gamification has a certain effect on the increase in the number of visited sightseeing spots and the days of stay in sightseeing spots. In this study, we developed "Supporting System for Visiting Sightseeing Spot Using Image Recognition and Processing Technology (KadaBingo)" and conducted the field experiment in Zentsuzi city, Kagawa Prefecture. This paper describes KadaBingo and analyzes travel behavior based on the data obtained from the field experiment. © 2020, Springer Nature Switzerland AG.

关键词： Image recognition

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An Android Application to Calculate the Average Chemical Presence in Food Items 1

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作者： Khan, Md. Nasfikur R. Khan, Moshiur Rahman Mashuk, A. K. Ehsanul Haque Sunny, Fahim Islam Farhan, S. K. Adif Shukhon, Ramendra Narayan Saha Depart of Electrical and Electronic Engineering Independent University Bangladesh Dhaka Bangladesh

ISBN: (数字)9783030423636

ISBN: (纸本)9783030423629;9783030423650

Mutilation of food items by the use of various chemicals in order to force it to achieve its mature state artificially and prevent the food item from withering out too early and increase shelf life, which also helps with the exporting of the food item to far distant places, thus adding more profit to the business. The problem is among these chemicals some do not wear off that easily and if the presence of the chemical residue is high enough, it can cause serious immediate or long term health complications for the consumer. The objective was to help the consumer with an app to figure out the average chemical presence in a variety of food items that can help the user with the necessary information about the food item on a per unit weight basis. The modern world is all about instant information, saving time & reliability and nothing serves better in these categories than the smart phones powered and turned into super devices by various Applications or "Apps" as we generally know. With the widespread availability of high speed internet, Apps has started to play a vital role in human day to day life, as our life is getting complex Apps serve us a good deal of playing the role of a personal assistant. Using Apps we can keep track of our physical and mental health, we can locate doctors in emergency, find blood donors in crucial moments, order groceries at home, find out the components of our consumed food, order food from the restaurants we prefer, order a ride to reach at our destination or even gather knowledge about the galaxy and stars way far beyond our reach. All of these activities can be done instantly without even moving an inch. Hence Apps can save a lot of time and effort, relieving us from our hectic life. © 2020, Springer Nature Switzerland AG.

关键词： Health

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A Model to Forecast the Student’s Grade and Course Recommendation: A Case Vietnamese Students 1

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作者： Nho, Minh Tu Nguyen, Hoa-Huy Cuong, Ton Quang Nguyen, Viet Anh VNU University of Engineering and Technology Vietnam National University Hanoi Viet Nam VNU Center for Education Accreditation Vietnam National University Hanoi Viet Nam VNU University of Education Vietnam National University Hanoi 144 Xuan Thuy Cau Giay Hanoi Viet Nam

ISBN: (数字)9783030385019

ISBN: (纸本)9783030385002;9783030385033

This paper presents a model for forecasting the learning outcomes and suggesting the recommend courses for undergraduate students. In this research, we propose methods based on machine learning techniques and recommender systems to answer three research questions of forecasting student’s outcomes problem: (1) How to forecast the course’s grade for the next subject. (2) How to predict the final grade point average basing on the subjects students have studied. (3) How to suggest a list of subjects that students should learn in the next semester. The model has been tested with the grade data in 22-course subjects with the participation of 580 students. The results, in the best case, for predicting the missing subject grades with the tested data set were 0.656, a good result for scores in the range [0, 10]. Assessing the user’s satisfaction of the model through the survey, the results show that 68.2% of students think that the system is useful for them. © 2020, Springer Nature Switzerland AG.

关键词： Students

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Parked Car Detection Method Based on Home Wireless LAN -Using Household Equipment to Detect a Parked Car- 1

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作者： Suzuki, Motoko Katsumata, Yuki Yamada, Akira NTT DOCOMO INC. 3-6 Hikari-no-oka Kanagawa Yokosuka-shi239-8536 Japan

ISBN: (数字)9783030539498

ISBN: (纸本)9783030539481;9783030539511

Consumer-to-consumer (C2C) car park sharing services are now widespread. In these services, space owners rent their unused land, e.g., an unused parking space next to the owner’s home, to a driver. Different from coin parking services, drivers using the park sharing services can make reservations through web sites or mobile-phone applications. There are drivers who abuse this system by, for example, overstaying their reservation. The high cost of parking space sensors that monitor the existence of a parked car makes it cost prohibitive for individuals to install these types of equipment to deter the abuse of parking spaces. To address this problem, we propose a parked car detection technique employing wireless LAN. The proposed method utilizes a household wireless LAN access point and a household laptop computer, and we monitor the received signal strength indicator (RSSI) of beacon frames. This unique method reduces the detection cost and will aid in proliferating car park sharing services. In this paper, we detect the existence of a car in a parking space using the mean and variance of the RSSI. The generated datasets are used for Support Vector Machine (SVM), Decision Tree, and the K-nearest neighbor algorithm (KNN) binary classification. We previously showed that a parked car can be detected when the locations of the equipment are the same. In this study, we show the effect of changing the equipment location in the house on the detection score. These results show that the best recall score is 0.88 and that changing the equipment location does not affect the recall score. The results of this study are expected to be used in a multimodal system. © 2020, Springer Nature Switzerland AG.

关键词： Location

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An analytics-Based Envelope Neural Net Approach to Forecasting Memory Leakage in an Enterprise Applications Environment 1

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作者： Khosla, Nitin Sharma, Dharmendra Performance Engineering ICTCAPM Department of Home Affairs Canberra Australia Computer Science University of Canberra Canberra Australia

ISBN: (数字)9783030423636

ISBN: (纸本)9783030423629;9783030423650

This paper investigates a model to forecast memory-leak behavior in a big applications environment with short time frames, using neural networks. This process predicts the likelihood of a memory leakage in an IT infrastructure, with large number of enterprise applications running in a real world, while analyzing the work-load demand patterns hidden in the transactional data of the enterprise applications. This approach generates synthetic workload profiles and then based upon extracted insights, predict memory leakage behavior under peak load and stress conditions. The approach is investigated also for capacity tuning of the existing infrastructure and future planning of the required infrastructure. Co-learning, is used to train models and their use in analyzing the workload patterns. The workload prediction has enormous potential to optimize resources with minimal risk. © 2020, Springer Nature Switzerland AG.

关键词： Neural networks

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Block Steganography Based Secure Key Encryption to Improve Data Security 1

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作者： Roy, Arindam Bhattacharya, Jayshree Kundu, Sayantani Sahana, Sudipta Singh, Dharmpal Department of Computer Science and Engineering JIS College of Engineering Nadia Kalyani741235 India

ISBN: (数字)9783030423636

ISBN: (纸本)9783030423629;9783030423650

In digital communication secure communication sessions must be provided. The data transmitted across the global network should be more secure so that any Intruder can’t interpret the data. To improve the security features in case of data transmission and data hiding Cryptography and Steganography are the two popular methods. In this paper, we are presenting the combination of Cryptography and Steganography techniques in one system. Our approach is to develop a new technique to encrypt secret information to cipher text and hide it into an image, with the benefits of combining cryptography and steganography. Firstly, the message is encrypted by using a Secret key and XOR its with the main text using binary representation. After that, we performed Steganography. Some modifications are done on LSB algorithm by adding a sequence algorithm for pixel selection. Results we get indicate that our proposed work is encouraging in terms of robustness and security. © 2020, Springer Nature Switzerland AG.

关键词： Steganography

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Identification of Neighbourhood Cities Based on Landuse Bigdata Using K-Means and K-NN Algorithm 1

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作者： VinilaKumari, S. Bhargavi, P. Jyothi, S. Department of Computer Science SPMVV Tirupati India

ISBN: (数字)9783030469399

ISBN: (纸本)9783030469382;9783030469412

In present days, several cloud computing platforms or web services such as Flip kart and Amazon, Google App Engine, blue cloud etc. provide a locally distributed and scalable data which is in uncountable form. But, these platforms do not regard geographical location data. However, the data is generated from the modern remote satellites with their geological topology. The so obtained geo-distributed database is able to process either a large scale data or a very simple type, scalable while being fault-tolerant and fast in answering a query. The processing of Big data includes the storing and analysing the uncountable amount of geographical data. The big data processing utilizes several programming models and frameworks such as Map Reduce, Hadoop, MongoDB, Pig etc. The present work concentrates on land use classification of various cities in India using geographical location data having latitude and longitude of every boundary. To perform this work, India map shape file with every state is used. The shape file is converted into longitude and latitude band information along with cities data. Nevertheless, the geo-graphical data is classified by applying the machine learning algorithms. © 2020, Springer Nature Switzerland AG.

关键词： Big data

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Bengali Poem Generation Using Deep learning Approach 1

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作者： Chy, Md. Kalim Amzad Rahman, Md. Abdur Masum, Abdul Kadar Muhammad Chowdhury, Shayhan Ameen Alam, Md. Golam Robiul Khan, Md. Shahidul Islam Department of Computer Science and Engineering International Islamic University Chittagong Chittagong Bangladesh Department of Computer Science and Engineering Dhaka Commerce College Dhaka Bangladesh

ISBN: (数字)9783030385019

ISBN: (纸本)9783030385002;9783030385033

This research proposes a deep learning based effective Bangla poem generation model that can generate any famous Bengali poet style poem. Unigram, bigram, and trigram word level approach has been followed to make the poem generation model, which is a very early study for this language. From various online website and social media about 35K Bangla poem containing more than 90 million words has been scrapped using python programming language. After preprocessing and tokenizing the data, text data is converted to the n-dimensional numerical vector space using word embedding tool. To build the language model various extension of Recurrent Neural Network (RNN) like LSTM, BiLSTM has experimented. Also, another merge mode for BiLSTM such as sum, avg, mul, concat has been tested. The generated poems are evaluated via various modern evaluation methods like BLEU, GLEU, and a Turing test. Among diverse neural network, BiLSTM performs better for unigram, bigram, trigram where for bigram it gives the best outcomes against BLEU and GLEU more than 87% and Turing test 89% satisfactory level. This study is an excellent contribution to the Bengali text generation research. © 2020, Springer Nature Switzerland AG.

关键词： Embeddings

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