Workload assignment for global real-time scheduling on unrelated clustered platforms

Real-Time Systems - Heterogeneous MPSoCs are being used more and more, from cellphones to critical embedded systems. Most of those systems offer heterogeneous sets of identical cores. In this...     

Fuzzy based multi-criteria vertical handover decision modeling in heterogeneous wireless networks

Vertical handover gain significant importance due to the enhancements in mobility models by the Fourth Generation (4G) technologies. However, these enhancements are limited to specific scenarios and hence do not provide support for generic mobility. Similarly, various schemes are proposed based on these mobility models but most of them are suffered from the high packet loss, frequent handovers, too early and late handovers, inappropriate network selection, etc. To address these challenges, a generic vertical handover management scheme for heterogeneous wireless networks is proposed in this article. The proposed scheme works in three phases. In the first phase, a handover triggering approach is designed to identify the appropriate place for initiating handover based on the estimated coverage area of a WLAN access point or cellular base station. In the second phase, fuzzy rule based system is designed to eliminate the inappropriate networks before deciding an optimal network for handover. In the third phase, a network selection scheme is developed based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision mechanism. Various parameters such as delay, jitter, Bit Error Rate (BER), packet loss, communication cost, response time, and network load are considered for selecting an optimal network. The proposed scheme is tested in a mobility scenario with different speeds of a mobile node ranging from very low to very high. The simulation results are compared with the existing decision models used for network selection and handover triggering approaches. The proposed scheme outperforms these schemes in terms of energy consumption, handover delay and time, packet loss, good put, etc.     

On Logical Foundations of Multilevel Secure Databases

It is envisaged that the application of the multilevel security (MLS) scheme will enhance flexibility and effectiveness of authorization policies in shared enterprise databases and will replace cumbersome authorization enforcement practices through complicated view definitions on a per user basis. However, the critical problem with the current model is that the belief at a higher security level is cluttered with irrelevant or inconsistent data as no mechanism for attenuation is supported. Critics also argue that it is imperative for MLS database users to theorize about the belief of others, perhaps at different security levels, an apparatus that is currently missing and the absence of which is seriously felt.The impetus for our current research is the need to provide an adequate framework for belief reasoning in MLS databases. In this paper, we show that these concepts can be captured in a F-logic style declarative query language, called MultiLog, for MLS deductive databases for which a proof theoretic, model theoretic and fixpoint semantics exist. This development is significant from a database perspective as it now enables us to compute the semantics of MultiLog databases in a bottom-up fashion. We also define a bottom-up procedure to compute unique models of stratified MultiLog databases. Finally, we establish the equivalence of MultiLog's three logical characterizations—model theory, fixpoint theory and proof theory.     

Deep features-based speech emotion recognition for smart affective services

Emotion recognition from speech signals is an interesting research with several applications like smart healthcare, autonomous voice response systems, assessing situational seriousness by caller affective state analysis in emergency centers, and other smart affective services. In this paper, we present a study of speech emotion recognition based on the features extracted from spectrograms using a deep convolutional neural network (CNN) with rectangular kernels. Typically, CNNs have square shaped kernels and pooling operators at various layers, which are suited for 2D image data. However, in case of spectrograms, the information is encoded in a slightly different manner. Time is represented along the x-axis and y-axis shows frequency of the speech signal, whereas, the amplitude is indicated by the intensity value in the spectrogram at a particular position. To analyze speech through spectrograms, we propose rectangular kernels of varying shapes and sizes, along with max pooling in rectangular neighborhoods, to extract discriminative features. The proposed scheme effectively learns discriminative features from speech spectrograms and performs better than many state-of-the-art techniques when evaluated its performance on Emo-DB and Korean speech dataset.

     

Destructive and non-destructive evaluation of concrete for optimum sand to aggregate volume ratio

Aggregates are the biggest contributor to concrete volume and are a crucial parameter in dictating its mechanical properties. As such, a detailed experimental investigation was carried out to evaluate the effect of sand-to-aggregate volume ratio (s/a) on the mechanical properties of concrete utilizing both destructive and non-destructive testing (employing UPV (ultrasonic pulse velocity) measurements). For investigation, standard cylindrical concrete samples were made with different s/a (0.36, 0.40, 0.44, 0.48, 0.52, and 0.56), cement content (340 and 450 kg/m³), water-to-cement ratio (0.45 and 0.50), and maximum aggregate size (12 and 19 mm). The effect of these design parameters on the 7, 14, and 28 d compressive strength, tensile strength, elastic modulus, and UPV of concrete were assessed. The careful analysis demonstrates that aggregate proportions and size need to be optimized for formulating mix designs; optimum ratios of s/a were found to be 0.40 and 0.44 for the maximum aggregate size of 12 and 19 mm, respectively, irrespective of the W/C (water-to-cement) and cement content.     

Darstellung und Koordinationsverhalten von 2-Acylmethylen-thiazolidinen

Preparation and Coordination Behaviour of 2-Acylmethylene-thiazolidines The reaction of 2,2-dichlorovinyl ketones with 2-aminoethanethiol in different solvents is described. The 2-acylmethylene-thiazolidines as the main products from this reaction are studied in view of their coordination tendency to divalent metal ions. The prepared neutral chelates with Cu²⁺, Ni²⁺, Co²⁺, Pd²⁺, Zn²⁺ have [N₂O₂] coordination, elucidated by analytical, spectroscopical and magnetochemical methods.     

Hierarchical steganography using novel optimum quantization technique

Security and imperceptibility are fundamental issues for steganography. This paper presents a multi-level steganography system based on concealing and deception. Basically, the secret image is embedded in a cover image, which in turn is embedded in another higher-level cover image. Each steganography level provides additional security, with lower levels implemented using stronger steganography methods. Furthermore, in the event that the higher level steganography is compromised, it would include misleading information to deceive the attacker that he/she is successfully eavesdropping. One challenge of hierarchical system is retaining hidden data in lower level in a higher level stenographic technique. To mitigate this issue, we designed a novel technique which combines discrete cosine transform and least significant bit (LSB). The technique objective is to maximize the capacity and invisibility of the secret image with minimal modification to the cover image (at most k-bits per block). The performance (capacity and peak signal-to-noise ratio) of the proposed method has superior performance compared with LSB since it combines the benefits of 1-bit and 3-bit LSBs. Furthermore, the paper demonstrates that the secret message is successfully embedded and extracted in two-level steganography system with peak signal-to-nose ratio greater than 20 dB.     

Comparative Analysis of Ti,Ni,and Au Electrodes on Characteristics of TiO2 Nanofibers for Humidity Sensor Application

The effect of metal（Ti,Ni,and Au） electrodes on humidity sensing properties of electrospun TiO₂ nanofibers was investigated in this work.The devices were fabricated by evaporating metal contacts on SiO₂ layer thermally grown on silicon substrate.The separation between the electrodes was 90μm for all sensors.The sensors were tested from 40%to 90%relative humidity（RH） by AC electrical characterization at room temperature. When sensors are switched between 40%and 90%RH,the corresponding response and recovery time are 3 s and 5 s for Ti-electrode sensor,4 s and 7 s for Ni-electrode sensor,and 7 s and 13 s for Au-electrode sensor.The hysteresis was 3%,5%and 15%for Ti-,Ni-,and Au-electrode sensor,respectively.The sensitivity of Ti,Ni,and Au-electrode sensors are 7.53 MΩ/%RH,5.29 MΩ/%RH and 4.01 MΩ/%RH respectively at 100 Hz.Therefore Ti-electrode sensor is found to have linear response,fast response and recovery time and higher sensitivity as compared with those of Ni- and Au-electrode sensors.Comparison of humidity sensing properties of sensors with different electrode material may propose a compelling route for designing and optimizing humidity sensors.     

Influence of different viscosity grade cellulose-based polymers on the development of valsartan controlled release tablets

This work is based on formulating and optimizing controlled release (CR) valsartan (160 mg) tablets using different viscosity grades of the cellulosic polymer. The objective was to develop an effective once-daily drug delivery system of this cardiovascular agent. Central composite design was used for designing the formulations. Polymers used were Methocel® K4M, K15M and K100M. Compatibility of excipients with active was studied through FT-IR. Micromeritic properties were determined and formulations exhibiting appropriate flow characteristics were compressed. Swelling behavior and in vitro buoyancy effect were studied and response surface curves were constructed to optimize the formulation. Multi-point dissolution profiles of valsartan CR tablets at pH 1.2, 4.5 and 6.8 were obtained. Model-dependent and model-independent methods were performed including f2, stability test as per ICH guidelines and ANOVA. FT-IR studies revealed the compatibility of valsartan with all excipients. Formulation K4T9 (containing 25% K4M polymer) was selected to be the best optimized trial, based on physical properties and controlled release profile (23% at 4 h, 82% at 16 h and 100% at 24 h). Results of buoyancy and swelling behavior indicated that HPMC-K4M polymer exhibited excellent floating lag time and swelling indexes. In vitro drug release kinetics showed that formulation K4T9 displayed Korsmeyer–Peppas drug release pattern with r value > 0.99. The manufacturing process of K4T9 was also found to be reproducible with a shelf life period of 41 and 36 months at room temperature and accelerated conditions, respectively. Valsartan CR matrix-based formulation was successfully prepared with Methocel K4M retardant.