Revisiting the size effect in software fault prediction models

In object oriented (OO) software systems, class size has been acknowledged as having an indirect effect on the relationship between certain characteristics, captured via metrics, and faultproneness . In particular, size appears to have a more significant mediation effect on CBO andFan-out than other metrics, although the evidence is not consistent in allexamined systems .…

Android OS CASE STUDY

Android is a mobile operating system based on a modified version of the Linux kernel and other open source software . It is an operating system forlow powered devices that run on battery and are full of hardware like GlobalPositioning System (GPS) receivers, cameras, light and orientation sensors, Wi-Fi and LTE (4G telephony) connectivity and a touch screen .…

VCGAN Video Colorization with Hybrid Generative Adversarial Network

Hybrid GenerativeAdversarial Network (VCGAN) addresses two prevalent issues in the videocolorization domain: Temporal consistency and unification of colorizationnetwork and refinement network into a single architecture . The hybrid VCGAN strikes a good balance between color vividness and videocontinuity . To improve the consistency of farframes, we propose a dense long-term loss that smooths the temporal disparity of every two remote frames.…

Represent Items by Items An Enhanced Representation of the Target Item for Recommendation

Item-based collaborative filtering (ICF) has been widely used in industrial applications such as recommender system and online advertising . In this paper, we propose an enhanced representation of the target item which distills relevant information from the co-occurrence items . With the enhanced representation, CER has strongerrepresentation power for the tail items compared to the state-of-the-art ICFmethods.…

Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging

The consideration of predictive uncertainty in medical imaging with deeplearning is of utmost importance . We apply $ \sigma $ scaling with a single scalarvalue; a simple, yet effective calibration method for both types ofuncertainty . The performance of our approach is evaluated on a variety of common medical regression data sets using different state-of-the-artconvolutional network architectures .…

Leaving My Fingerprints Motivations and Challenges of Contributing to OSS for Social Good

Growing interest in open source software has also been attributed to developers deciding to use their technical skills to benefit a commonsocietal good . Researchers conducted 21semi-structured interviews with OSS for Social Good (OSS4SG) contributors . They found that OSS4SG contributors focus less on benefiting themselves by padding their resumewith new technology skills and are more interested in leaving their mark on society at statistically significant levels .…

Android OS CASE STUDY

Android is a mobile operating system based on a modified version of the Linux kernel and other open source software . It is an operating system forlow powered devices that run on battery and are full of hardware like GlobalPositioning System (GPS) receivers, cameras, light and orientation sensors, Wi-Fi and LTE (4G telephony) connectivity and a touch screen .…

Model Guided Road Intersection Classification

Understanding complex scenarios from in-vehicle cameras is essential for safely operating autonomous driving systems in densely populated areas . Intersection areas are one of the most critical as they concentrate aconsiderable number of traffic accidents and fatalities . Detecting and understanding the scene configuration of these usually crowded areas is then ofextreme importance for both autonomous vehicles and modern ADAS aimed at preventing road crashes and increasing the safety of vulnerable road users .…

Cloud computing as a platform for monetizing data services A two sided game business model

The role of the cloud should be reshaped from being a passive virtual market to become an active platform for monetizing the big data through Artificial Intelligence (AI) services . The objective is to enable the cloud to help big data service providers reach a wider set of customers and cloud users to be exposed to a larger and richer variety of data to run their data analytic tasks .…

Efficient Hyperparameter Optimization for Physics based Character Animation

Physics-based character animation has seen significant advances in recent years with the adoption of Deep Reinforcement Learning (DRL) However,DRL-based learning methods are usually computationally expensive . Tuninghyperparameters for these methods often requires repetitive training of controlpolicies . In this work, we propose a novel Curriculum-based Multi-Fidelity Bayesian Optimization framework .…

A Sliding Window Approach to Automatic Creation of Meeting Minutes

Meeting minutes record any subject matters discussed, decisions reached andactions taken at meetings . Sliding window approach aims to tackle issues associated with thenature of spoken text, including lengthy transcripts and lack of documentstructure . Approach combines a sliding window and a neuralabstractive summarizer to navigate through the transcripts to find salient content .…

Stochastic Recurrent Neural Network for Multistep Time Series Forecasting

Time series forecasting based on deep architectures has been gaining popularity in recent years due to their ability to model complex non-lineartemporal dynamics . The recurrent neural network is one such model capable of handling variable-length input and output . In our model design, the transition function of therecurrent neural network, which determines the evolution of the hidden states, is stochastic rather than deterministic as in a regular recurrent neuralnetwork .…

Android OS CASE STUDY

Android is a mobile operating system based on a modified version of the Linux kernel and other open source software . It is an operating system forlow powered devices that run on battery and are full of hardware like GlobalPositioning System (GPS) receivers, cameras, light and orientation sensors, Wi-Fi and LTE (4G telephony) connectivity and a touch screen .…

Reconfigurable Adaptive Channel Sensing

Channel sensing consists of probing the channel from time to time to check whether or not it is active – say of an incoming message . When communication is sparse with information being sent once in a long while,channel sensing becomes a significant source of energy consumption .…

To mock a Mocking bird Studies in Biomimicry

This paper dwells on certain novel game-theoretic investigations inbio-mimicry . The model is used to study the situation where multi-armedbandit predators with zero prior information are introduced into the ecosystem . The prey can be either nutritious or toxic to the predator, but the prey may signal (possibly) deceptively without revealing its true “type” The model uses a model to study a panmictic ecosystem occupied by species of prey with a relatively short lifespan, which evolve mimicry signals over generations .…

Designing Optimal Key Lengths and Control Laws for Encrypted Control Systems based on Sample Identifying Complexity and Deciphering Time

There has been no systematic methodology of constructing cyber-physical systems that can achieve desired control performance while being protected against eavesdropping attacks . We propose a systematic method for designing the both of an optimal key length and an optimal controller to maximize both of the controlperformance and the difficulty of the identification .…

On the Nature of Issues in Five Open Source Microservices Systems An Empirical Study

There is a limited evidence-based and thorough understanding of the types of issues faced by microservices system developers and causes that trigger the issues . Technicaldebt (321), Build (145), Security (137) and Serviceexecution and communication (119) are prominent . “General programming errors”, “Poor security management”, “invalidconfiguration and communication”, and “Legacy versions, compatibility anddependency” are the predominant causes for the leading four issue categories .…

Spatially Coherent Clustering Based on Orthogonal Nonnegative Matrix Factorization

Classical approaches in cluster analysis are typically based on a featurespace analysis . Many applications lead to datasets with additionalspatial information and ground truth with spatially coherent classes . We propose several approaches with different optimization techniques, where the TV regularization is either performed as a subsequent postprocessing step or included into the clustering algorithm .…

An Adaptive Learning based Generative Adversarial Network for One To One Voice Conversion

Voice Conversion (VC) deals with conversion of vocal style of one speaker to another speaker while keeping the linguistic contentsunchanged . VC task is performed through a three-stage pipeline consisting of speech analysis, speech feature mapping, and speech reconstruction . ALGAN-VC framework consists of some approaches to improve speech quality and voice similarity between source and target speakers .…

OPTION OPTImization Algorithm Benchmarking ONtology

Different platforms for benchmarking optimization algorithms use different data models and formats, which drastically inhibits identification of relevant data sets, their interpretation, and their interoperability . We report in this paper on the development of such an ontology, which we nameOPTION (OPTImization algorithm benchmarking ONtology) Our ontology providesthe vocabulary needed for semantic annotation of the core entities involved inthe benchmarking process, such as algorithms, problems, and evaluationmeasures .…

Math Operation Embeddings for Open ended Solution Analysis and Feedback

Feedback on student answers and even during intermediate steps in solving questions is an important element in math education . Such feedback can help students correct their errors and ultimately lead toimproved learning outcomes . Most existing approaches for automated studentsolution analysis and feedback require manually constructing cognitive models and anticipating student errors for each question .…

Prior free Strategic Multiagent Scheduling with focus on Social Distancing

The algorithm takes input from citizens and schedules the store’s time-slots based on their importance to visit the facility . We show that it reduces the socialcongestion significantly using users’ visit data from a store . The problem becomes NP-complete as soon as the multi-slot demands are indivisibleand provide a polynomial-time mechanism that is truthful, individuallyrational, and approximately optimal .…

Normal Driven Spherical Shape Analogies

This paper introduces a new method to stylize 3D geometry . The key observation is that the surface normal is an effective instrument to capturedifferent geometric styles . This formulation can deform a 3D shape intodifferent styles within a single framework .…

Low rank Tensor Estimation via Riemannian Gauss Newton Statistical Optimality and Second Order Convergence

In this paper, we consider the estimation of a low Tucker rank tensor from anumber of noisy linear measurements . The general problem covers many specificexamples arising from applications, including tensor regression, tensorcompletion, and tensor PCA/SVD . We propose a Riemannian Gauss-Newton (RGN)method with fast implementations for low Tucker Rank tensor estimation .…