A new data embedding method for mpeg layer III audio steganography

A new method of MP3 steganography is proposed with emphasis on increasing the steganography capacity of the carrier medium. This paper proposes a data embedding algorithm to hide more information for compressed bitstream of MP3 audio files. The sign bits of Huffman codes are selected as the stego-object according to the Huffman coding characteristic in region of Count1. Embedding process does not require the main MP3 audio file during the extraction of hidden message and the size of MP3 file cannot be changed in this step. Our proposed method caused much higher information embedding capacity with lower computational complexity compared with MP3Stego tools. Experimental results show an excellent imperceptibility for the new algorithm

Subjective Evaluation of Music Compressed with the ACER Codec Compared to AAC, MP3, and Uncompressed PCM

Audio data compression has revolutionised the way in which the music industry and musicians sell and distribute their products. Our previous research presented a novel codec named ACER (Audio Compression Exploiting Repetition), which achieves data reduction by exploiting irrelevancy and redundancy in musical structure whilst generally maintaining acceptable levels of noise and distortion in objective evaluations. However, previous work did not evaluate ACER using subjective listening tests, leaving a gap to demonstrate its applicability under human audio perception tests. In this paper, we present a double-blind listening test that was conducted with a range of listeners (N=100). The aim was to determine the efficacy of the ACER codec, in terms of perceptible noise and spatial distortion artefacts, against de facto standards for audio data compression and an uncompressed reference. Results show that participants reported no perceived differences between the uncompressed, MP3, AAC, ACER high quality, and ACER medium quality compressed audio in terms of noise and distortions but that the ACER low quality format was perceived as being of lower quality. However, in terms of participants’ perceptions of the stereo field, all formats under test performed as well as each other, with no statistically significant differences. A qualitative, thematic analysis of listeners’ feedback revealed that the noise artefacts that produced the ACER technique are different from those of comparator codecs, reflecting its novel approach. Results show that the quality of contemporary audio compression systems has reached a stage where their performance is perceived to be as good as uncompressed audio. The ACER format is able to compete as an alternative, with results showing a preference for the ACER medium quality versions over WAV, MP3, and AAC. The ACER process itself is viable on its own or in conjunction with techniques such as MP3 and AAC

Efficient Analysis in Multimedia Databases

The rapid progress of digital technology has led to a situation where computers have become ubiquitous tools. Now we can find them in almost every environment, be it industrial or even private. With ever increasing performance computers assumed more and more vital tasks in engineering, climate and environmental research, medicine and the content industry. Previously, these tasks could only be accomplished by spending enormous amounts of time and money. By using digital sensor devices, like earth observation satellites, genome sequencers or video cameras, the amount and complexity of data with a spatial or temporal relation has gown enormously. This has led to new challenges for the data analysis and requires the use of modern multimedia databases. This thesis aims at developing efficient techniques for the analysis of complex multimedia objects such as CAD data, time series and videos. It is assumed that the data is modeled by commonly used representations. For example CAD data is represented as a set of voxels, audio and video data is represented as multi-represented, multi-dimensional time series. The main part of this thesis focuses on finding efficient methods for collision queries of complex spatial objects. One way to speed up those queries is to employ a cost-based decompositioning, which uses interval groups to approximate a spatial object. For example, this technique can be used for the Digital Mock-Up (DMU) process, which helps engineers to ensure short product cycles. This thesis defines and discusses a new similarity measure for time series called threshold-similarity. Two time series are considered similar if they expose a similar behavior regarding the transgression of a given threshold value. Another part of the thesis is concerned with the efficient calculation of reverse k-nearest neighbor (RkNN) queries in general metric spaces using conservative and progressive approximations. The aim of such RkNN queries is to determine the impact of single objects on the whole database. At the end, the thesis deals with video retrieval and hierarchical genre classification of music using multiple representations. The practical relevance of the discussed genre classification approach is highlighted with a prototype tool that helps the user to organize large music collections. Both the efficiency and the effectiveness of the presented techniques are thoroughly analyzed. The benefits over traditional approaches are shown by evaluating the new methods on real-world test datasets

Genetic algorithm and tabu search approaches to quantization for DCT-based image compression

Today there are several formal and experimental methods for image compression, some of which have grown to be incorporated into the Joint Photographers Experts Group (JPEG) standard. Of course, many compression algorithms are still used only for experimentation mainly due to various performance issues. Lack of speed while compressing or expanding an image, poor compression rate, and poor image quality after expansion are a few of the most popular reasons for skepticism about a particular compression algorithm. This paper discusses current methods used for image compression. It also gives a detailed explanation of the discrete cosine transform (DCT), used by JPEG, and the efforts that have recently been made to optimize related algorithms. Some interesting articles regarding possible compression enhancements will be noted, and in association with these methods a new implementation of a JPEG-like image coding algorithm will be outlined. This new technique involves adapting between one and sixteen quantization tables for a specific image using either a genetic algorithm (GA) or tabu search (TS) approach. First, a few schemes including pixel neighborhood and Kohonen self-organizing map (SOM) algorithms will be examined to find their effectiveness at classifying blocks of edge-detected image data. Next, the GA and TS algorithms will be tested to determine their effectiveness at finding the optimum quantization table(s) for a whole image. A comparison of the techniques utilized will be thoroughly explored

Using algorithmic information theory and stochastic modeling to improve classification and evolutionary computation: a dissertation submitted to the department of computer science of the Universidad Autonoma de Madrid in partial fulfillment of the requirements for the degree of doctor of philosophy

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, junio de 200

Human spatial navigation in the digital era: Effects of landmark depiction on mobile maps on navigators’ spatial learning and brain activity during assisted navigation

Navigation was an essential survival skill for our ancestors and is still a fundamental activity in our everyday lives. To stay oriented and assist navigation, our ancestors had a long history of developing and employing physical maps that communicated an enormous amount of spatial and visual information about their surroundings. Today, in the digital era, we are increasingly turning to mobile navigation devices to ease daily navigation tasks, surrendering our spatial and navigational skills to the hand-held device. On the flip side, the conveniences of such devices lead us to pay less attention to our surroundings, make fewer spatial decisions, and remember less about the surroundings we have traversed. As navigational skills and spatial memory are related to adult neurogenesis, healthy aging, education, and survival, scientists and researchers from multidisciplinary fields have made calls to develop a new account of mobile navigation assistance to preserve human navigational abilities and spatial memory. Landmarks have been advocated for special attention in developing cognitively supportive navigation systems, as landmarks are widely accepted as key features to support spatial navigation and spatial learning of an environment. Turn-by-turn direction instructions without reference to surrounding landmarks, such as those provided by most existing navigation systems, can be one of the reasons for navigators’ spatial memory deterioration during assisted navigation. Despite the benefit of landmarks in navigation and spatial learning, long-standing literature on cognitive psychology has pointed out that individuals have only a limited cognitive capacity to process presented information for a task. When the learning items exceed learners’ capacity, the performance may reach a plateau or even drop. This leads to an unexamined yet important research question on how to visualize landmarks on a mobile map to optimize navigators’ cognitive resource exertion and thus optimize their spatial learning. To investigate this question, I leveraged neuropsychological and hypothesis-driven approaches and investigated whether and how different numbers of landmarks depicted on a mobile map affected navigators’ spatial learning, cognitive load, and visuospatial encoding. Specifically, I set out a navigation experiment in three virtual urban environments, in which participants were asked to follow a given route to a specific destination with the aid of a mobile map. Three different numbers of landmarks—3, 5, and 7—along the given route were selected based on cognitive capacity literature and presented to 48 participants during map-assisted navigation. Their brain activity was recorded both during the phase of map consultation and during that of active locomotion. After navigation in each virtual city, their spatial knowledge of the traversed routes was assessed. The statistical results revealed that spatial learning improved when a medium number of landmarks (i.e., five) was depicted on a mobile map compared to the lowest evaluated number (i.e., three) of landmarks, and there was no further improvement when the highest number (i.e., seven) of landmarks were provided on the mobile map. The neural correlates that were interpreted to reflect cognitive load during map consultation increased when participants were processing seven landmarks depicted on a mobile map compared to the other two landmark conditions; by contrast, the neural correlates that indicated visuospatial encoding increased with a higher number of presented landmarks. In line with the cognitive load changes during map consultation, cognitive load during active locomotion also increased when participants were in the seven-landmark condition, compared to the other two landmark conditions. This thesis provides an exemplary paradigm to investigate navigators’ behavior and cognitive processing during map-assisted navigation and to utilize neuropsychological approaches to solve cartographic design problems. The findings contribute to a better understanding of the effects of landmark depiction (3, 5, and 7 landmarks) on navigators’ spatial learning outcomes and their cognitive processing (cognitive load and visuospatial encoding) during map-assisted navigation. Of these insights, I conclude with two main takeaways for audiences including navigation researchers and navigation system designers. First, the thesis suggests a boundary effect of the proposed benefits of landmarks in spatial learning: providing landmarks on maps benefits users’ spatial learning only to a certain extent when the number of landmarks does not increase cognitive load. Medium number (i.e., 5) of landmarks seems to be the best option in the current experiment, as five landmarks facilitate spatial learning without taxing additional cognitive resources. The second takeaway is that the increased cognitive load during map use might also spill over into the locomotion phase through the environment; thus, the locomotion phase in the environment should also be carefully considered while designing a mobile map to support navigation and environmental learning

2020 Program and Abstracts for the Celebration of Student Scholarship

Program and Abstracts from the Celebration of Student Scholarship held in the Spring of 2020

From Bugs to Decision Support – Leveraging Historical Issue Reports in Software Evolution

Software developers in large projects work in complex information landscapes and staying on top of all relevant software artifacts is an acknowledged challenge. As software systems often evolve over many years, a large number of issue reports is typically managed during the lifetime of a system, representing the units of work needed for its improvement, e.g., defects to fix, requested features, or missing documentation. Efficient management of incoming issue reports requires the successful navigation of the information landscape of a project. In this thesis, we address two tasks involved in issue management: Issue Assignment (IA) and Change Impact Analysis (CIA). IA is the early task of allocating an issue report to a development team, and CIA is the subsequent activity of identifying how source code changes affect the existing software artifacts. While IA is fundamental in all large software projects, CIA is particularly important to safety-critical development. Our solution approach, grounded on surveys of industry practice as well as scientific literature, is to support navigation by combining information retrieval and machine learning into Recommendation Systems for Software Engineering (RSSE). While the sheer number of incoming issue reports might challenge the overview of a human developer, our techniques instead benefit from the availability of ever-growing training data. We leverage the volume of issue reports to develop accurate decision support for software evolution. We evaluate our proposals both by deploying an RSSE in two development teams, and by simulation scenarios, i.e., we assess the correctness of the RSSEs' output when replaying the historical inflow of issue reports. In total, more than 60,000 historical issue reports are involved in our studies, originating from the evolution of five proprietary systems for two companies. Our results show that RSSEs for both IA and CIA can help developers navigate large software projects, in terms of locating development teams and software artifacts. Finally, we discuss how to support the transfer of our results to industry, focusing on addressing the context dependency of our tool support by systematically tuning parameters to a specific operational setting

Drivers, Measures and Outcomes of Luxury Flagship Store Experience

The luxury flagship store experience (LFSE) and luxury flagship store attributes (LFSA) involve multi-faceted aspects that have received reasonably less attention in the extant literature. This thesis attempts to dive deep into the topic of the ‘luxury flagship store experience’, extending the concept in terms of dimensions, drivers and outcomes. The research comprises mixed-methods studies to attain the research objectives. The findings revealed three dimensions of the LFSE and four for the LFSA constructs. This study also assessed the model constructs’ relationships and tested 22 hypotheses. The research findings offer a better understanding of consumer responses during shopping at, or visiting, a luxury flagship store and contribute to the extant body of knowledge in several ways

Efficiency in audio processing : filter banks and transcoding

Audio transcoding is the conversion of digital audio from one compressed form A to another compressed form B, where A and B have different compression properties, such as a different bit-rate, sampling frequency or compression method. This is typically achieved by decoding A to an intermediate uncompressed form, and then encoding it to B. A significant portion of the involved computational effort pertains to operating the synthesis filter bank, which is an important processing block in the decoding stage, and the analysis filter bank, which is an important processing block in the encoding stage. This thesis presents methods for efficient implementations of filter banks and audio transcoders, and is separated into two main parts. In the first part, a new class of Frequency Response Masking (FRM) filter banks is introduced. These filter banks are usually characterized by comprising a tree-structured cascade of subfilters, which have small individual filter lengths. Methods of complexity reduction are proposed for the scenarios when the filter banks are operated in single-rate mode, and when they are operated in multirate mode; and for the scenarios when the input signal is real-valued, and when it is complex-valued. An efficient variable bandwidth FRM filter bank is designed by using signed-powers-of-two reduction of its subfilter coefficients. Our design has a complexity an order lower than that of an octave filter bank with the same specifications. In the second part, the audio transcoding process is analyzed. Audio transcoding is modeled as a cascaded quantization process, and the cascaded quantization of an input signal is analyzed under different conditions, for the MPEG 1 Layer 2 and MP3 compression methods. One condition is the input-to-output delay of the transcoder, which is known to have an impact on the audio quality of the transcoded material. Methods to reduce the error in a cascaded quantization process are also proposed. An ultra-fast MP3 transcoder that requires only integer operations is proposed and implemented in software. Our implementation shows an improvement by a factor of 5 to 16 over other best known transcoders in terms of execution speed