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"The team around the student" - About the environmental therapist's competence as a support for the teacher
Get PDFDetecting malware by analyzing app permissions on Android platform : a systematic literature review
Get PDFSmartphone adaptation in society has been progressing at a very high speed. Having the ability to run on a vast variety of devices, much of the user base possesses an Android phone. Its popularity and flexibility have played a major role in making it a target of different attacks via malware, causing loss to users, both financially and from a privacy perspective. Different malware and their variants are emerging every day, making it a huge challenge to come up with detection and preventive methodologies and tools. Research has spawned in various directions to yield effective malware detection mechanisms. Since malware can adopt different ways to attack and hide, accurate analysis is the key to detecting them. Like any usual mobile app, malware requires permission to take action and use device resources. There are 235 total permissions that the Android app can request on a device. Malware takes advantage of this to request unnecessary permissions, which would enable those to take malicious actions. Since permissions are critical, it is important and challenging to identify if an app is exploiting permissions and causing damage. The focus of this article is to analyze the identified studies that have been conducted with a focus on permission analysis for malware detection. With this perspective, a systematic literature review (SLR) has been produced. Several papers have been retrieved and selected for detailed analysis. Current challenges and different analyses were presented using the identified articles. View Full-Text Keywords: malware detection, static analysis, hybrid analysis, permissions analysispublishedVersio
Code smell detection using ensemble machine learning algorithms
Get PDFCode smells are the result of not following software engineering principles during software development, especially in the design and coding phase. It leads to low maintainability. To evaluate the quality of software and its maintainability, code smell detection can be helpful. Many machine learning algorithms are being used to detect code smells. In this study, we applied five ensemble machine learning and two deep learning algorithms to detect code smells. Four code smell datasets were analyzed: the Data class, the God class, the Feature-envy, and the Long-method datasets. In previous works, machine learning and stacking ensemble learning algorithms were applied to this dataset and the results found were acceptable, but there is scope of improvement. A class balancing technique (SMOTE) was applied to handle the class imbalance problem in the datasets. The Chi-square feature extraction technique was applied to select the more relevant features in each dataset. All five algorithms obtained the highest accuracy—100% for the Long-method dataset with the different selected sets of metrics, and the poorest accuracy, 91.45%, was achieved by the Max voting method for the Feature-envy dataset for the selected twelve sets of metrics. Keywords: code smell, code smell detection, ensemble method, deep learning, Chi-square feature extraction technique, SMOTE class balancing techniquepublishedVersio
The chatbot usability scale : the design and pilot of a usability scale for interaction with AI-based conversational agents
Get PDFStandardised tools to assess a user’s satisfaction with the experience of using chatbots and conversational agents are currently unavailable. This work describes four studies, including a systematic literature review, with an overall sample of 141 participants in the survey (experts and novices), focus group sessions and testing of chatbots to (i) define attributes to assess the quality of interaction with chatbots and (ii) the designing and piloting a new scale to measure satisfaction after the experience with chatbots. Two instruments were developed: (i) A diagnostic tool in the form of a checklist (BOT-Check). This tool is a development of previous works which can be used reliably to check the quality of a chatbots experience in line with commonplace principles. (ii) A 15-item questionnaire (BOT Usability Scale, BUS-15) with estimated reliability between .76 and .87 distributed in five factors. BUS-15 strongly correlates with UMUX-LITE by enabling designers to consider a broader range of aspects usually not considered in satisfaction tools for non-conversational agents, e.g. conversational efficiency and accessibility, quality of the chatbot’s functionality and so on. Despite the convincing psychometric properties, BUS-15 requires further testing and validation. Designers can use it as a tool to assess products, thus building independent databases for future evaluation of its reliability, validity and sensitivity.publishedVersio
The role of incumbents in energy transitions : investigating the perceptions and strategies of the oil and gas industry
Get PDFThe study focuses on sustainability transitions in the oil and gas industry, particularly its strategies and perceptions towards mitigating climate change. The paper offers a quantitative analysis of survey data collected from 116 questionnaire responses involving representatives of oil and gas companies, academia and young professionals, supplemented by a qualitative analysis of selected companies' reports and outlooks. The empirical results show that the oil and gas industry is attentive towards climate change and has the capacity to transit towards sustainability. There are significant differences in how the industry perceives climate change mitigation policies and treats public debate on climate change, which can be explained by geography and the related socio-political context. We point to the importance of stability of macroeconomic factors, such as oil prices, for oil and gas companies to diversify and transit, as well as underline the need to gain a deeper understanding of the effect of external pressures. We argue for clearer and more inclusive regulation, coordination and dissemination for climate policies, and wider engagement of oil and gas companies in sustainable energy transition. This paper contributes with a meso-level assessment of sustainability transitions, and suggests a more diverse picture of incumbents by highlighting the need to revise their role in sustainability transition processes. We offer additional perspectives on transition pathways for policymakers. Keywords: Oil, natural gas, climate change, sustainable energy transition, industry perspectivepublishedVersio
Weighted iterated local branching for mathematical programming problems with binary variables
Get PDFLocal search algorithms are frequently used to handle complex optimization problems involving binary decision variables. One way of implementing a local search procedure is by using a mixed-integer programming solver to explore a neighborhood defined through a constraint that limits the number of binary variables whose values are allowed to change in a given iteration. Recognizing that not all variables are equally promising to change when searching for better neighboring solutions, we propose a weighted iterated local branching heuristic. This new procedure differs from similar existing methods since it considers groups of binary variables and associates with each group a limit on the number of variables that can change. The groups of variables are defined using weights that indicate the expected contribution of flipping the variables when trying to identify improving solutions in the current neighborhood. When the mixed-integer programming solver fails to identify an improving solution in a given iteration, the proposed heuristic may force the search into new regions of the search space by utilizing the group of variables that are least promising to flip. The weighted iterated local branching heuristic is tested on benchmark instances of the optimum satisfiability problem, and computational results show that the weighted method is superior to an alternative method without weights.publishedVersio
