Information, Volume 7, Issue 4 (December 2016) – 20 articles

The Monster group, the biggest of the sporadic groups, is equipped with the highest known number of dimensions and symmetries. Taking into account variants of the Borsuk–Ulam theorem and a novel topological approach cast in a physical fashion that has the potential to be operationalized, the universe can be conceived as a lower-dimensional manifold encompassed in the Monster group. Our universe might arise from spontaneous dimension decrease and symmetry breaking that occur inside the very structure of the Monster Module. We elucidate how the energetic loss caused by projection from higher to lower dimensions and by the Monster group’s non-abelian features is correlated with the present-day asymmetry in the thermodynamic arrow. By linking the Monster Module to its theoretical physical counterparts, it is then possible to calculate its enthalpy and Lie group trajectories. Our approach also reveals how a symmetry break might lead to a universe based on multi-dimensional string theories and CFT/AdS (anti-de Sitter/conformal field theory) correspondence. Full article

Human activity recognition has been a hot topic in recent years. With the advances in sensor technology, there has been a growing interest in using smartphones equipped with a set of built-in sensors to solve tasks of activity recognition. However, in most previous studies, smartphones were used with a fixed position—like trouser pockets—during recognition, which limits the user behavior. In the position-independent cases, the recognition accuracy is not very satisfactory. In this paper, we studied human activity recognition with smartphones in different positions and proposed a new position-independent method called PACP (Parameters Adjustment Corresponding to smartphone Position), which can markedly improve the performance of activity recognition. In PACP, features were extracted from the raw accelerometer and gyroscope data to recognize the position of the smartphone first; then the accelerometer data were adjusted corresponding to the position; finally, the activities were recognized with the SVM (Support Vector Machine) model trained by the adjusted data. To avoid the interference of smartphone orientations, the coordinate system of the accelerometer was transformed to get more useful information during this process. Experimental results show that PACP can achieve an accuracy over 91%, which is more effective than previous methods. Full article

In Delay-Tolerant Networks (DTNs), nodes may be selfish and reluctant to expend their precious resources on forwarding messages for others. Therefore, an incentive scheme is necessary to motivate selfish nodes to cooperatively forward messages. However, the current incentive schemes mainly focus on encouraging nodes to participate in message forwarding, without considering the node congestion problem. When many messages are forwarded to the nodes with high connection degree, these nodes will become congested and deliberately discard messages, which will seriously degrade the routing performance and reduce the benefits of other nodes. To address this problem, we propose a credit-based congestion-aware incentive scheme (CBCAIS) for DTNs. In CBCAIS, a check and punishment mechanism is proposed to prevent forwarding nodes from deliberately discarding message. In addition, a message acceptance selection mechanism is proposed to allow the nodes to decide whether to accept other messages, according to self congestion degree. The experimental results show that CBCAIS can effectively stimulate selfish nodes to cooperatively forward messages, and achieve a higher message delivery ratio with lower overhead ratio, compared with other schemes. Full article

The research on non-cooperative multiuser multiple-input multiple-output with space-time block code (MIMO-STBC) communication systems is a challenging and important task. However, to our knowledge, there is little report of this topic. Being two key research issues in this area, modulation classification and user number detection are studied in this paper. We consider both problems jointly as a multiple hypothesis testing problem. Based on this idea, we propose a joint modulation classification and user number detection algorithm for the multiuser MIMO-STBC systems. The proposed method does not require prior knowledge of the propagation channel or noise power, and thus might be suitable for the non-cooperative scenario. Simulations validate the effectiveness of the proposed method. Full article

Inspired by the overwhelming success of Histogram of Oriented Gradients (HOG) features in many vision tasks, in this paper, we present an innovative compact feature descriptor called fuzzy Histogram of Oriented Lines (f-HOL) for action recognition, which is a distinct variant of the HOG feature descriptor. The intuitive idea of these features is based on the observation that the slide area of the human body skeleton can be viewed as a spatiotemporal 3D surface, when observing a certain action being performed in a video. The f-HOL descriptor possesses an immense competitive advantage, not only of being quite robust to small geometric transformations where the small translation and rotations make no large fluctuations in histogram values, but also of not being very sensitive under varying illumination conditions. The extracted features are then fed into a discriminative conditional model based on Latent-Dynamic Conditional random fields (LDCRFs) to learn to recognize actions from video frames. When tested on the benchmark Weizmann dataset, the proposed framework substantially supersedes most existing state-of-the-art approaches, achieving an overall recognition rate of 98.2%. Furthermore, due to its low computational demands, the framework is properly amenable for integration into real-time applications. Full article

Citizen engagement and participation are a key focus for government and government agencies, and with the advent of Internet technologies questions arise about the role and impact of technology on citizen participation. This paper aims to explore the role of technology in citizen participation within schools. This research used in-depth comparative case studies using examples from two different schools and school systems, one in the United Kingdom and one in Indonesia. The wider school systems are complex and dynamic environments with multiple stakeholders, media, and supporting systems, and the schools operate under geopolitical and social influences. This paper provides a framework, based on Actor-Network Theory (ANT), for capturing e-participation in schools, particularly identifying the influence of technology as a conduit for enabling, engaging, and empowering stakeholders. Full article

Over the past couple of decades, global positioning system (GPS) technology has been utilized to collect large-scale data from travel surveys. As the precise spatiotemporal characteristics of travel could be provided by GPS devices, the issues of traditional travel survey, such as misreporting and non-response, could be addressed. Considering the defects of dedicated GPS devices (e.g., the need for a large sum of money to buy devices, forgetfulness in the taking of devices to collect data, limiting of the sample size because of the number of devices, etc.), and the fact that the smartphone is becoming one of the necessities of life, there is an opportunity for smartphones to replace dedicated GPS devices. Although several general reviews of GPS travel survey and GPS data-processing methods have been written, a systematic review of smartphone-based GPS data collection and travel mode detection has not be made.. The studies were collected from six databases. The purpose of this review is to critically evaluate the current literature on the existing methodologies of travel mode detection based on GPS raw data collected by smartphones. Meanwhile, according to a systematic comparison of the different methods of data preprocessing for travel mode detection, this paper details the strengths and weaknesses of the existing methods. Furthermore, it is a very important step towards developing methodologies and applications for GPS raw data collected by smartphones. Full article

Although the importance of advocacy activities by civil society organizations (CSOs) in policy and decision-making procedures has been greatly emphasized in the literature of political science and social policy, we have relatively little understanding of the relevance and impact of the leading actors who structure the diverse networks and discourses through social media; further recognition is needed in both fields. The purpose of this study is to analyze civil society organizations at the local government level involved in advocacy activities through the use of social media such as Facebook and Twitter. Our study focuses on a specific Japanese Facebook community page—the “Tsukuba Civic Activities Cyber-Square”—aimed at enhancing civil society activities in Japan. This page is operated by the municipal government of Tsukuba, in collaboration with the University of Tsukuba and Intel Corporation. Our findings indicate that social networking services such as Facebook can provide civil society organizations with: (1) more political opportunities to advocate; (2) more chances to connect with the local government; and (3) create opportunities to exert greater presence, despite their limited financial and political resources. Full article

Collaboration with citizens and users plays an increasing role in the transformation of public services towards new forms of production and delivery. Thus there is a need to modernize the civil service to accelerate innovation in governments, as civil servants will also have an important role to play. Digital civic engagement platforms can provide a more attractive and accessible means for participation. We believe that neither an exclusive top-down approach nor a bottom-up approach can address the current needs. Instead a hybrid approach should be designed. This paper presents a novel approach to address the issue of current civic disengagement. This approach is illustrated through four different use cases in the Swiss context. Full article

To depict the influence of decision makers’ risk psychology on the interval-valued intuitionistic fuzzy multi-criteria decision-making process, this paper proposes a new method based on prospect theory. Considering the risk attitude of the decision maker, we transform interval-valued intuitionistic fuzzy numbers into real numbers via a prospect value function and consequently derive the prospect decision matrices. Regarding the criteria weights that are incompletely known or completely unknown, a new nonlinear optimization model is developed to determine the criteria weights by considering the subjective and objective factors. Furthermore, we calculate the prospect projection of each alternative for the ideal solution and rank all the alternatives according to the prospect projection values. Finally, an example is provided to illustrate the application of the developed approach. Full article

The demand for communicating large amounts of data in real-time has raised new challenges with implementing high-speed communication paths for high definition video and sensory data. It requires the implementation of high speed data paths based on hardware. Implementation difficulties have to be addressed by applying new techniques based on data-oriented algorithms. This paper focuses on a solution for this problem by applying a lossless data compression mechanism on the communication data path. The new lossless data compression mechanism, called LCA-DLT, provides dynamic histogram management for symbol lookup tables used in the compression and the decompression operations. When the histogram memory is fully used, the management algorithm needs to find the least used entries and invalidate these entries. The invalidation operations cause the blocking of the compression and the decompression data stream. This paper proposes novel techniques to eliminate blocking by introducing a dynamic invalidation mechanism, which allows achievement of a high throughput data compression. Full article

The interplay between retrocausality and the time-reversal symmetry of the dynamical law of quantum mechanics underscores the significance of the measurement dynamics with the use of indivisible and discrete quantum particles to be mediated. One example of empirical evidence demonstrating the significance of retrocausality going along with time-reversal symmetry is seen in the operation of a reaction cycle to be expected in chemical evolution. A reaction cycle can hold itself when the causative operation of the cycle remains robust, even when facing frequent retrocausal interventions of a quantum-mechanical origin. Quantum mechanics in and of itself has potential in raising a reaction cycle in the prebiotic phase of chemical evolution, even without any help of artefactual scaffoldings of an external origin. Full article

Near-infrared (NIR) face recognition has attracted increasing attention because of its advantage of illumination invariance. However, traditional face recognition methods based on NIR are designed for and tested in cooperative-user applications. In this paper, we present a convolutional neural network (CNN) for NIR face recognition (specifically face identification) in non-cooperative-user applications. The proposed NIRFaceNet is modified from GoogLeNet, but has a more compact structure designed specifically for the Chinese Academy of Sciences Institute of Automation (CASIA) NIR database and can achieve higher identification rates with less training time and less processing time. The experimental results demonstrate that NIRFaceNet has an overall advantage compared to other methods in the NIR face recognition domain when image blur and noise are present. The performance suggests that the proposed NIRFaceNet method may be more suitable for non-cooperative-user applications. Full article

Physical-layer security is now being considered for information protection in future wireless communications. However, a better understanding of the inherent secrecy of wireless systems under more realistic conditions, with a specific attention to the relative energy consumption costs, has to be pursued. This paper aims at proposing new analysis tools and investigating the relation between secrecy capacity and energy consumption in a 3rd Generation Partnership Project (3GPP) cellular network , by focusing on secure and energy efficient communications. New metrics that bind together the secure area in the Base Station (BS) sectors, the afforded date-rate and the power spent by the BS to obtain it, are proposed that permit evaluation of the tradeoff between these aspects. The results show that these metrics are useful in identifying the optimum transmit power level for the BS, so that the maximum secure area can be obtained while minimizing the energy consumption. Full article

The modern encryption methods are reliable if strong keys (passwords) are used, but the human factor issue cannot be solved by cryptographic methods. The best variant is binding all authenticators (passwords, encryption keys, and others) to the identities. When a user is authenticated by biometrical characteristics, the problem of protecting a biometrical template stored on a remote server becomes a concern. The paper proposes several methods of generating keys (passwords) by means of the fuzzy extractors method based on signature parameters without storing templates in an open way. Full article

With the rise of social media platforms based on the sharing of pictures and videos, the question of how such platforms should be studied arises. Previous research on social media (content) has mainly focused on text (written words) and the rather text-based social media platforms Twitter and Facebook. Drawing on research in the fields of visual, political, and business communication, we introduce a methodological framework to study the fast-growing image-sharing service Instagram. This methodological framework was developed to study political parties’ Instagram accounts and tested by means of a study of Swedish political parties during the 2014 election campaign. In this article, we adapt the framework to also study other types of organizations active on Instagram by focusing on the following main questions: Do organizations only use Instagram to share one-way information, focusing on disseminating information and self-presentation? Or is Instagram used for two-way communication to establish and cultivate organization-public relationships? We introduce and discuss the coding of variables with respect to four clusters: the perception of the posting, image management, integration, and interactivity. Full article

The ever increasing growth of the production of high-throughput sequencing data poses a serious challenge to the storage, processing and transmission of these data. As frequently stated, it is a data deluge. Compression is essential to address this challenge—it reduces storage space and processing costs, along with speeding up data transmission. In this paper, we provide a comprehensive survey of existing compression approaches, that are specialized for biological data, including protein and DNA sequences. Also, we devote an important part of the paper to the approaches proposed for the compression of different file formats, such as FASTA, as well as FASTQ and SAM/BAM, which contain quality scores and metadata, in addition to the biological sequences. Then, we present a comparison of the performance of several methods, in terms of compression ratio, memory usage and compression/decompression time. Finally, we present some suggestions for future research on biological data compression. Full article

In recent years, a wide range of Business Intelligence (BI) technologies have been applied to different areas in order to support the decision-making process. BI enables the extraction of knowledge from the data stored. The healthcare industry is no exception, and so BI applications have been under investigation across multiple units of different institutions. Thus, in this article, we intend to analyze some open-source/free BI tools on the market and their applicability in the clinical sphere, taking into consideration the general characteristics of the clinical environment. For this purpose, six BI tools were selected, analyzed, and tested in a practical environment. Then, a comparison metric and a ranking were defined for the tested applications in order to choose the one that best applies to the extraction of useful knowledge and clinical data in a healthcare environment. Finally, a pervasive BI platform was developed using a real case in order to prove the tool viability. Full article

The Park Geun-hye Administration of Korea (2013–2017) aims to increase the level of transparency and citizen trust in government through the Government 3.0 initiative. This new initiative for public sector innovation encourages citizen-government collaboration and collective intelligence, thereby improving the quality of policy-making and implementation and solving public problems in a new way. However, the national initiative that identifies collective intelligence and citizen-government collaboration alike fails to understand what the wisdom of crowds genuinely means. Collective intelligence is not a magic bullet to solve public problems, which are called “wicked problems”. Collective deliberation over public issues often brings pain and patience, rather than fun and joy. It is not so easy that the public finds the best solution for soothing public problems through collective deliberation. The Government 3.0 initiative does not pay much attention to difficulties in gathering scattered wisdom, but rather highlights uncertain opportunities created by collective interactions and communications. This study deeply discusses the weaknesses in the logic of, and approach to, collective intelligence underlying the Government 3.0 initiative in Korea and the overall influence of the national initiative on participatory democracy. Full article

The purpose of this study was to survey access to information for learning on the types of assistive technology used by undergraduate students with disabilities in Northern Thailand. The types of assistive technology in this study included assistive devices and educational services. Data were collected from a questionnaire developed as a rating scale checklist that was completed by 140 undergraduate students with disabilities. Results of this study found that all types of educational services provided more to undergraduate students with disabilities than almost all kinds of assistive technology. Additionally, the students utilized assistive devices and accessed educational services for different reasons, and most students with visual disabilities were given either assistive devices or educational services. In terms of use, results found that students with hearing disabilities used assistive technology the most, whereas findings concerning needs showed that all of the students with disabilities demanded almost all types of assistive technology. Full article