Reviewerly/exHarmony huggingface dataset:
VisCrime

Open multidimensional data from existing sources and social media often carries insightful information on social issues. With the increase of high volume data and the proliferation of visual analytics platforms, users can more easily interact with and pick out meaningful information from a large dataset. In this paper, we present VisCrime, a system that uses visual analytics to maps out crimes that have occurred in a region/neighbourhood. VisCrime is underpinned by a novel trajectory algorithm that is used to create trajectories from open data sources that reports incidents of crime and data gathered from social media. Our system can be accessed at http://viscrime.ml/deckmap
The Effects of Second Life on the Motivation of EFL Student Teachers

This study aimed at investigating the effects of using a virtual world, Second Life (SL), on the motivation of Turkish EFL student teachers. First, a 10-week real-life task syllabus was designed and conducted in SL. Focus-group interviews were utilized to enhance the quality of the tasks. Then, the effects of SL on motivation were tracked via qualitative research tools, namely semi-structured interviews, weekly evaluation forms, and observations. The findings showed that SL was effective in increasing motivation of the participating student teachers. The characteristics of the virtual world that were reported to have an effect on motivation were as follows: natural environment, realistic places, anxiety-free environment, excitement, and visual support. This chapter provides possibilities for those who are interested in employing virtual world technologies in foreign/second language teaching and learning and finally describes an investigation into the role of the virtual world in relation to affordances such technologies present across the globe.
Distributed person re-identification through network-wise rank fusion consensus

The problem of re-identify persons across single disjoint camera-pairs has received great attention from the community. Despite this, when the re-identification process has to be carried out on a wide camera network additional problems arise and deny the direct application of existing solutions. Thus, a different approach has to be considered. In particular, existing approaches have neglected the importance of the network topology (i.e., the configuration of the monitored area) in such a process. To try filling such a gap, we propose a distributed person re-identification framework which brings in the following contributions: (i) a weighted camera matching cost that measures the re-identification performance between cameras in the network; (ii) a derivation of the distance vector algorithm that yields to network topology learning and allows us to prioritize and limit the cameras inquired for the re-identification; (iii) a network consensus weighted rank fusion solution that allows us to perform the re-identification in a robust fashion. Results on four benchmark datasets show that the proposed approach brings to significant network-wise re-identification improvements.
Analysis of similar weather conditions to improve reuse in weather-based decision support systems

Weather-based decision support systems (DSSs) are being built to improve the efficiency of the production systems in the domains of healthcare, agriculture, transport, governance and so on. Normally, a weather condition (WC) is represented by the statistical values of weather variables for a given duration (e.g. a day or a week). In a weather-based DSS, given a WC, the domain experts prepare the appropriate suggestions to improve the efficiency of the stakeholders. Normally, once the domain experts prepare a suggestion for a given WC that belongs to certain period (e.g. year or season), there is a scope to reuse the same suggestion for the similar WCs of other period(s). As a result, the performance of the DSS could be improved. In this paper, to improve reuse, we have proposed a notion of category-based WC (CWC) which is formed by using the categories of weather variables in the respective domain. By considering the context of agromet advisory service operated by India Meteorological Department (IMD) and the corresponding weather categories provided by IMD, we have analyzed the extent of reuse among CWCs by conducting the experiments on 30 years of weather data collected at Rajendranagar, Hyderabad, Telangana state. The experiments are conducted by considering two types of CWCs with the duration equal to one day and five days. By varying the number of weather variables in CWC from one to five, we have computed the extent of reuse among CWCs of different periods of the following period types: year, season, and phenophases (i.e., growth stages) of the Rice crop. The results show that there is a significant similarity among the CWCs of the given period and the CWCs of the preceding periods of each period type. For any domain including agriculture, the results provide an opportunity to improve the efficiency of weather-based agricultural DSSs by improving the reuse of the weather-based suggestions.
Supercover Semantics for Deontic Action Logic

The semantics for a deontic action logic based on Boolean algebra is extended with an interpretation of action expressions in terms of sets of alternative actions, intended as a way to model choice. This results in a non-classical interpretation of action expressions, while sentences not in the scope of deontic operators are kept classical. A deontic structure based on Simons’ supercover semantics is used to interpret permission and obligation. It is argued that these constructions provide ways to handle various problems related to free choice permission. The main result is a sound and complete axiomatization of the semantics.
Digital Image Inpainting by Estimating Wavelet Coefficient Decays From Regularity Property and Besov Spaces

Inpainting methods play a major role in image processing, minimizing the effects of data block loss in image transmission. They analyze primarily the spatial correlation between the portions of an image, usually without explicitly exploring information on the frequency domain. Techniques that evaluate losses of blocks in images do not locally describe a figure of merit for consistent measurement of spatial correlation between pixels of each corrupted block. This investigation presents a digital image inpainting technique, extensible to video applications, using the property of wavelet regularity in multiresolution image analysis, described locally in the sense of Besov vector spaces. Their generalized smoothness allows widespread changes in wavelet coefficients of image data, concealing errors in visual information. This technique estimates decay curves of wavelet coefficients from pixels, based in the observation of the regularity property, correcting pixel blocks contaminated by noise. This investigation proposes an algorithm in the wavelet transform domain, which detects and fixes damaged pixel blocks from a designed decay function for wavelet coefficients. Simulation results, obtained in corrupted images by several noise patterns, indicated better performance of this methodology when compared with other ones.
Error Detection Technique for A Median Filter Using Denoising Algorithm

This paper presents a modified design for error detection technique for a median filter, while processing the images using a digital processing system, acquisition stage capture impulsive noises along with the images. A classic filter used to eliminate. Some sliding windows of n × n matrices are created from the original image. The generated median is compared with the original pixel value at the center of the selected portion of the matrix corresponding to the image. If we found any error then the new median value is placed instead of the existing one. For storing the pixel values, a line buffer and register bank are used along with the median filter. Using the buffers the time taken for the median calculation is reduced, and as a result the total time taken for processing the image is also reduced.
If it is easy to remember, then it is not secure: Metacognitive beliefs affect password selection

Summary In this research, we applied current theories of metacognition to study computer security and tested the idea that users' password selection is affected by the metacognitive belief that if a password is memorable, then it is not secure. In two experiments, different types of eight‐character passwords and longer, more secure sentences were presented. Participants rated perceived memorability and perceived security of the passwords and indicated whether they would use them in a critical and in a noncritical service. The results confirmed the belief. Sentences that are in fact highly secure and perceived as highly memorable were also perceived as weak passwords. The belief strongly affected password selection for critical services, but it had no effect on noncritical services. In sum, long sentences are a particularly interesting type of password because they meet both security and memorability criteria, but their use is limited by a false belief.
Evaluating Mobile Instant Messaging for L2 Development

This chapter presents a longitudinal investigation of the use of mobile instant messaging (MIM) to develop second language skills in the foreign language classroom. A three-year investigation is presented where the author attempted to analyze the potential of the application to provide language opportunities and foster interaction in the target language. WhatsApp application is used as a virtual platform where its multimodal characteristics are exploited in order to expand students' in-class time. Thus, one text-based and two voice-based WhatsApp groups are analyzed trough an experimental design with control and experimental groups. Statistical analysis as well as a systematic tracking of the messages sent throughout the interaction were implemented to observe any potential language benefit in the participants. Results indicated that students experienced an improvement in terms of accuracy as well as different speaking skills; nevertheless, task design was found to be fundamental to encourage participation and interaction.
Behavioral Biometrics in Mobile Banking and Payment Applications

This paper presents an overview on the possible use of behavioral biometrics methods in mobile banking and payment applications. As mobile applications became more common, more and more users conduct payments using their smartphones. While requiring secure services, the customers often do not lock their devices and expose them to potential misuse and theft. Banks and financial institutions apply multiple anti-fraud and authentication systems - but to ensure the required usability, they must develop new ways to authenticate their users and authorize transactions. Answer to this problem comes with a family of behavioral biometric methods which can be utilized to secure those applications without hindering the usability. The goal of this paper is to describe potential areas in which behavioral biometrics can be used to ensure more secure mobile payments, increase usability and prevent frauds.
Shuffle and Mix: On the Diffusion of Randomness in Threshold Implementations of Keccak

Threshold Implementations are well known as a provably first-order secure Boolean masking scheme even in the presence of glitches. A precondition for their security proof is a uniform input distribution at each round function, which may require an injection of fresh randomness or an increase in the number of shares. However, it is unclear whether violating the uniformity assumption causes detectable leakage in practice. Recently, Daemen undertook a theoretical study of lossy mappings to extend the understanding of uniformity violations. We complement his work by entropy simulations and practical measurements of Keccak's round function. Our findings shed light on the necessity of mixing operations in addition to bit-permutations in a cipher's linear layer to propagate randomness between S-boxes and prevent exploitable leakage. Finally, we argue that this result cannot be obtained by current simulation methods, further stressing the continued need for practical leakage measurements.
Ambient Intelligence in Smart City Environments: Topologies and Information Architectures

ManyAmbient Intelligence (AmI) cities aroundSmart the world haveSmart City embarked on ambitiousTopologies programmesInformation Architectures towards creating SmartSmart CitiesSmart City where information, diverse digital opportunities, and collective intelligenceIntelligence can be harnessed ubiquitously. Smart Cities are conceptualized using citywide smart and intelligent architectures informed by the context in which they are implemented. These architectures make it possible to access information and intelligence anywhere and at any time. Information processing and computing is embedded within the urban infrastructures to a point where immovable city entities such as traffic lights are more intelligent to make real-time decisions based on the happenings in the environmentEnvironment in which they are deployed. Advanced development of ambient computing within the realm of Smart Cities will further culminate into possibilities such as vehicle-to-vehicle communicationVehicle-to-vehicle communication (V2V) and mobile-to-mobile (M2M) communication. Using extensive and critical literature review, this chapter specifically focusses on the designDesign of information architectures that will ultimately support the enshrining of spatial intelligence within Smart City environments hinged on the internet of thingsInternet of Things (IoT) (IoT) and cloud/fog computing. The chapter presents latest trends in the research and practice of ambient intelligence (AmI) (AmI) linked to the realization of the key principles of Smart Cities from the information topology and architecture point of view. A conceptual ambient intelligence architecture that highlights the building blocks of any ambient intelligence architecture as deployed in Smart City environments is also proposed. The proposed conceptual architecture can be used as a blueprint in the design of ambient intelligence topologies and architectures in different contextual settings.
Factorization patterns on nonlinear families of univariate polynomials over a finite field

We estimate the number $$|\mathcal {A}_{{\varvec{\lambda }}}|$$ of elements on a nonlinear family $$\mathcal {A}$$ of monic polynomials of $$\mathbb {F}_{q}[T]$$ of degree r having factorization pattern $${\varvec{\lambda }}:=1^{\lambda _1}2^{\lambda _2}\ldots r^{\lambda _r}$$. We show that $$|\mathcal {A}_{{\varvec{\lambda }}}|= \mathcal {T}({\varvec{\lambda }})\,q^{r-m}+\mathcal {O}(q^{r-m-{1}/{2}})$$, where $$\mathcal {T}({\varvec{\lambda }})$$ is the proportion of elements of the symmetric group of r elements with cycle pattern $${\varvec{\lambda }}$$ and m is the codimension of $$\mathcal {A}$$. We provide explicit upper bounds for the constants underlying the $$\mathcal {O}$$-notation in terms of $${\varvec{\lambda }}$$ and $$\mathcal {A}$$ with “good” behavior. We also apply these results to analyze the average-case complexity of the classical factorization algorithm restricted to $$\mathcal {A}$$, showing that it behaves as good as in the general case.
Liminal Worlds: Presence and Performer Agency in Tele-Collaborative Interaction

This chapter explores theories of presence, and performer agency in tele-collaborative interaction, and their application to intercultural tele-improvisation. It examines theories of listening and perception in distributed performance contexts and considers issues of spatiality, temporality and time consciousness. Included in this investigation are practitioner perspectives and examples from case study performance that reveal how participants conceptualised networked space and time as the activity of the music, rather than being external to it. The chapter concludes by reviewing definitions of networked space, third space, and cyberspace, and how our perception and cognition of online space occurs through the actions and social practices (e.g., improvisation) with which we engage.
Secure Digital Databases using Watermarking based on English-Character Attributes

Introduction: The single space and the double space (DS). In this procedure, an image is used to watermark a digital database, where the image bytes are divided into binary strings that block the text attributes of the selected database, we proposed an algorithm to defend against four common database attacks. Objective: Perform the watermark is Embedding and makes extraction of the watermark. We also describe the principal of the Embedding and extraction the watermark. Methods: The procedure to extract the watermark does not require knowledge of the original database that does not carry the same watermark. This feature is extremely important because it allows the discovery of a watermark in a copy of the original database, regardless of the subsequent updates to the asset. The extraction procedure is a direct reflection of the procedure used to embed the watermark is six steps. Results: Using new algorithm ability to develop a database watermark that would make it difficult for an attacker to remove or change the watermark without discovering the value of the object. To be judged effective, the database algorithm had to be able to create a strong enough watermark that could sustain the security of the database in the face of the following four types of attack: deletion of a sub-dataset, addition of a sub-dataset. Conclusion: The performance of the proposed algorithm was assessed in respect of its ability to defend the database against four common attacks for all tuples selection.
Content-Based Image Retrieval Using Hybrid Feature Extraction Techniques

Images consist of visual components such as color, shape, and texture. These components stand as the primary basis with which images are distinguished. A content-based image retrieval system extracts these primary features of an image and checks the similarity of the extracted features with those of the image given by the user. A group of images similar to the query image fed is obtained as a result. This paper proposes a new methodology for image retrieval using the local descriptors of an image in combination with one another. HSV histogram, Color moments, Color auto correlogram, Histogram of Oriented Gradients, and Wavelet transform are used to form the feature descriptor. In this work, it is found that a combination of all these features produces promising results that supersede previous research. Supervised learning algorithm, SVM is used for classification of the images. Wang dataset is used to evaluate the proposed system.
Intelligent conditional collaborative private data sharing

With the advent of distributed systems, secure and privacy-preserving data sharing between different entities (individuals or organizations) becomes a challenging issue. There are several real-world scenarios in which different entities are willing to share their private data only under certain circumstances, such as sharing the system logs when there is indications of cyber attack in order to provide cyber threat intelligence. Therefore, over the past few years, several researchers proposed solutions for collaborative data sharing, mostly based on existing cryptographic algorithms. However, the existing approaches are not appropriate for conditional data sharing, i.e., sharing the data if and only if a pre-defined condition is satisfied due to the occurrence of an event. Moreover, in case the existing solutions are used in conditional data sharing scenarios, the shared secret will be revealed to all parties and re-keying process is necessary. In this work, in order to address the aforementioned challenges, we propose, a “conditional collaborative private data sharing” protocol based on Identity-Based Encryption and Threshold Secret Sharing schemes. In our proposed approach, the condition based on which the encrypted data will be revealed to the collaborating parties (or a central entity) could be of two types: (i) threshold, or (ii) pre-defined policy. Supported by thorough analytical and experimental analysis, we show the effectiveness and performance of our proposal.
Analysis of Web Workload on QoS to Assist Capacity

Workload characterization is a well-established discipline, which finds its applications in performance evaluation of modern Internet services. With the high degree of popularity of the Internet, there is a huge variation in the intensity of workload and this opens up new challenging performance issues to be addressed. Internet Services are subject to huge variations in demand, with bursts coinciding with the times that the service has the most value. Apart from these flash crowds, sites are also subject to denial-of-service (DoS) attacks that can knock a service out of commission. The paper aims to study the effect of various workload distributions with the service architecture 'thread-per-connection' in use as a basis. The source model is structured as a sequence of activities with equal execution time requirement with an additional load time of page (loading embedded objects, images, etc.). The threads are allocated to the requests in the queue; leftover requests if any are denied service. The rejection rate is used as a criterion for evaluation of the performance of the system with a given capacity. The proposed model could form a basis for various system models to be integrated into the system and get its performance metrics (i.e. QoS) evaluated.
Color Image Encryption: A New Public Key Cryptosystem Based on Polynomial Equation

Image security is the need of today's era. The security task is being convoluted as there are a variety of data to secure as different levels of data security is needed based on the data type. Encryption is the maximum expedient approach to guarantee the safety of images over public networks. We have proposed a new public key cryptosystem based on polynomial equation. This approach has been desired because of their resistance to the cryptanalysis attacks. Parameters such as correlation coefficient, entropy, histogram analysis are used for the efficiency of our proposed method. The theoretic and simulation result provides a high quantity of protection. Thus, it is suitable for practical use in secure communication.