The fiscal burden of increasing social security expenses for the elderly is a major issue in Japan. The elderly lose physical fitness as they age. In particular, degradation in walking ability leads to falling acciden...
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ISBN:
(纸本)9781728138862
The fiscal burden of increasing social security expenses for the elderly is a major issue in Japan. The elderly lose physical fitness as they age. In particular, degradation in walking ability leads to falling accidents which pose a risk of serious wounds such as fractures that may resign one to a life in bed. In this study, we propose a system that is capable of measuring and analyzing an elderly person's walking ability. The proposed system, using Kinect motion sensor and written in the programming language Scratch, can measure an elderly person's gait accurately and be operated simply without specialist knowledge. Through real experiments with 16 subjects, some potential problems in walking were easily found by analyzing the measured data.
Program comprehension is a dominant process in software development and maintenance. Experts are considered to comprehend the source code efficiently by directing their gaze, or attention, to important components in i...
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In this paper, we present a novel attack against authorship attribution of source code. We exploit that recent attribution methods rest on machine learning and thus can be deceived by adversarial examples of source co...
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Cyber Physical Systems (CPSs) are a category of systems of systems (SoS) that integrate physical and computational elements. Such systems have existed for some time, but rigorous design methodologies for CPSs are scar...
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Cyber Physical Systems (CPSs) are a category of systems of systems (SoS) that integrate physical and computational elements. Such systems have existed for some time, but rigorous design methodologies for CPSs are scarce. The typical design process of a CPS makes use of a large number of models to help answer the wide range of design questions that arise in development. In other words, the design process produces models that describe the various crucial aspects, scopes and system components on different level of detail and abstraction. These partial models can potentially be coupled for effective information propagation across the different modeling perspectives to increase design reliability. However, they are usually expressed in different specialized tools and programminglanguages as a consequence of the system heterogeneity and the preference of the numerous designers involved. This paper therefore proposes generating abstractions of detailed sub-models, and then embedding those abstractions into system-wide models formulated in other formalisms.
Adapting rule sets to different settings, yet avoiding uncontrolled proliferation of variations, is a key challenge of rule management. One fundamental concept to foster reuse and simplify adaptation is inheritance. B...
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ISBN:
(纸本)9783030026714;9783030026707
Adapting rule sets to different settings, yet avoiding uncontrolled proliferation of variations, is a key challenge of rule management. One fundamental concept to foster reuse and simplify adaptation is inheritance. Building on rule modules, i.e., rule sets with input and output schema, we formally define inheritance of rule modules by incremental modification in single inheritance hierarchies. To avoid uncontrolled proliferation of modifications, we introduce formal modification restrictions which flexibly regulate the degree to which a child module may be modified in comparison to its parent. As concrete rule language, we employ Datalog(+/-) which can be regarded a common logical core of many rule languages. We evaluate the approach by a proof-of-concept prototype.
Functional logic languages can solve equations over user-defined data and functions. Thus, the definition of an appropriate meaning of equality has a long history in these languages, ranging from reflexive equality in...
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Identification of Fake News is import now a days because it is affecting our social life and opinions. Public misinformation detection is complicated task especially Pakistani media Fake News classification. We have s...
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ISBN:
(纸本)9781728146836
Identification of Fake News is import now a days because it is affecting our social life and opinions. Public misinformation detection is complicated task especially Pakistani media Fake News classification. We have seen Fake News in every aspect of life like politics, sports, business, entertainment and many more. For identification of fake news, we have done popular news websites scrap and develop our corpus of 344 News articles and labeled it manually Fake or True. We have investigated two feature extraction techniques like Term Frequency (TF) and Term Frequency-Inverse Document Frequency (TF-IDF). Seven different supervised Machine Learning (ML) classification algorithms are used and their results comparison have done. Best performance classifier K Nearest Neighbors (KNN) gives 70% accuracy and logistic regression gives 69% accuracy. Results can improved further by increasing number of articles in corpus.
In Model-Driven Engineering (MDE), models are used to build and analyze complex systems. In the last decades, different modelling formalisms have been proposed for supporting software development. However, their adopt...
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ISBN:
(纸本)9781728151267
In Model-Driven Engineering (MDE), models are used to build and analyze complex systems. In the last decades, different modelling formalisms have been proposed for supporting software development. However, their adoption and practice strongly rely on mastering essential modelling skills to develop a complete and coherent model-based system. Moreover, it is often difficult for novice modellers to get direct and timely feedback and recommendations on their modelling strategies and decisions, particularly in large classroom settings which hinders their learning. Certainly, there is an opportunity to apply Artificial Intelligence (AI) techniques to an MDE learning environment to empower the provisioning of automated and intelligent modelling advocacy. In this paper, we propose a framework called ModBud (a modelling buddy) to educate novice modellers about the art of abstraction. ModBud uses natural language processing (NLP) and machine learning (ML) to create modelling bots with the aim of improving the modelling skills of novice modellers and assisting other practitioners, too. These bots could be used to support teaching with automatic creation or grading of models and enhance learning beyond the traditional classroom-based MDE education with timely feedback and personalized tutoring. Research challenges for the proposed framework are discussed and a research roadmap is presented.
Intelligent IoT-based ambient assisted living systems (AALS) have been a major research focus area in recent times. Application of machine learning in areas of AALS such as fall detection has the potential to have hug...
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ISBN:
(数字)9781728104027
ISBN:
(纸本)9781728104034
Intelligent IoT-based ambient assisted living systems (AALS) have been a major research focus area in recent times. Application of machine learning in areas of AALS such as fall detection has the potential to have huge social impact. There has been active research in the application of machine learning in fall detection, using data generated by various means such as wearable devices, environment sensors and vision based systems. The main challenge is to create a model that detects falls accurately, while keeping the design of the fall detection system minimal and non-intrusive. Wearable devices equipped with inertial motion unit (IMU) sensors and vital signs sensors are commonly used to enable analysis around performance of machine learning (ML) models. In this paper, we analyze the impact of using IMU sensor parameters in combination with vital signs parameters, on the performance of ML algorithms for fall detection. We present details on the data set we have generated for this purpose, and compare the performance of various ML algorithms on the collected dataset, with features from IMU sensors vis-à-vis those from IMU sensors in combination with vital signs sensors. We also apply machine learning algorithms on two public datasets, one with only IMU sensor parameter values and the second with only vital signs parameter values, and summarize their performance.
Maiboli is a proposed programming language solution based on Marathi Devanagari script. It aims to bring the knowledge of programming to common individuals who find language as a barrier while learning programming. He...
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ISBN:
(纸本)9781538674765
Maiboli is a proposed programming language solution based on Marathi Devanagari script. It aims to bring the knowledge of programming to common individuals who find language as a barrier while learning programming. Here, the proposed system will be based on Python programming language and it will cover up basic libraries required for one to learn programming as a concept. This research paper serves insights of how Maiboli as a programming method, will serve for the well being of common individuals residing in areas where Marathi Language is dominant.
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