Search results for: composite signal

Authors: Aysun Sezer

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Magnetic Resonance Imaging (MRI) is one of the advanced diagnostic tools for evaluating shoulder pathologies. Proton Density (PD)-weighted MRI sequences prove highly effective in detecting edema. However, they are deficient in the anatomical identification of bones due to a trauma-induced decrease in signal-to-noise ratio and blur in the traumatized cortices. Computer-based diagnostic systems require precise segmentation, identification, and localization of anatomical regions in medical imagery. Deep learning-based object detection algorithms exhibit remarkable proficiency in real-time object identification and localization. In this study, the YOLOv8 model was employed to detect humeral head and scapular regions in 665 axial PD-weighted MR images. The YOLOv8 configuration achieved an overall success rate of 99.60% and 89.90% for detecting the humeral head and scapula, respectively, with an intersection over union (IoU) of 0.5. Our findings indicate a significant promise of employing YOLOv8-based detection for the humerus and scapula regions, particularly in the context of PD-weighted images affected by both noise and intensity inhomogeneity.

Keywords: YOLOv8, object detection, humerus, scapula, IRM

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Authors: Cinthia Campoverde, Mateo Benavidez, Victor Arias, Milton Torres

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This article evaluates and compares three propagation models: the Okumura-Hata model, the Ericsson 9999 model, and the SUI model. The inclusion of vegetation attenuation in the area is also taken into account. These mathematical models aim to predict the power loss between a transmitting antenna (Tx) and a receiving antenna (Rx). The study was conducted in the open areas of the Livestock Department at the Escuela Superior Politécnica de Chimborazo (ESPOCH) University, located in the city of Riobamba, Ecuador. The necessary parameters for each model were calculated, considering LTE technology. The transmitting antenna belongs to the mobile phone company ”TUENTI” in Band 2, operating at a frequency of 1940 MHz. The reception power data in the area were empirically measured using the ”Network Cell Info” application. A total of 170 samples were collected, distributed across 19 radius, forming concentric circles around the transmitting antenna. The results demonstrate that the Okumura Hata urban model provides the best fit to the measured data.

Keywords: propagation models, reception power, LTE, power losses, correction factor

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Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

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Super-resolution is the technique of intelligently upscaling images, avoiding artifacts or blurring, and deals with the recovery of a high-resolution image from one or more low-resolution images. Single-image super-resolution is a process of obtaining a high-resolution image from a set of low-resolution observations by signal processing. While super-resolution has been demonstrated to improve image quality in scaled down images in the image domain, its effects on the Fourier-based technique remains unknown. Super-resolution substantially improved the spatial resolution of the patient LGE images by sharpening the edges of the heart and the scar. This paper aims at investigating the effects of single image super-resolution on Fourier-based and image based methods of scale-up. In this paper, first, generate a training phase of the low-resolution image and high-resolution image to obtain dictionary. In the test phase, first, generate a patch and then difference of high-resolution image and interpolation image from the low-resolution image. Next simulation of the image is obtained by applying convolution method to the dictionary creation image and patch extracted the image. Finally, super-resolution image is obtained by combining the fused image and difference of high-resolution and interpolated image. Super-resolution reduces image errors and improves the image quality.

Keywords: image dictionary creation, image super-resolution, LGE images, patch extraction

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Authors: Tokihiko Akita, Seiichi Mita

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A millimeter-wave radar is the most robust against adverse environments, making it an essential environment recognition sensor for automated driving. However, the reflection signal is sparse and unstable, so it is difficult to obtain the high recognition accuracy. Deep learning provides high accuracy even for them in recognition, but requires large scale datasets with ground truth. Specially, it takes a lot of cost to annotate for a millimeter-wave radar. For the solution, utilizing a simulator that can generate an annotated huge dataset is effective. Simulation of the radar is more difficult to match with real world data than camera image, and recognition by deep learning with higher-order features using the simulator causes further deviation. We have challenged to improve the accuracy of traffic participant classification by fusing simulator and real-world data with domain adaptation technique. Experimental results with the domain adaptation network created by us show that classification accuracy can be improved even with a few real-world data.

Keywords: millimeter-wave radar, object classification, deep learning, simulation, domain adaptation

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Authors: Johannes Bibinger, Sebastian Eibl, Hans-Joachim Gudladt

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This study considers the influence of different irradiation scenarios on the thermal degradation of carbon fiber-reinforced polymers (CFRP). Real threats are simulated, such as fires with long-lasting low heat fluxes and nuclear heat flashes with short-lasting high heat fluxes. For this purpose, coated and uncoated quasi-isotropic samples of the commercially available CFRP HexPly® 8552/IM7 are thermally irradiated from one side by a cone calorimeter and a xenon short-arc lamp with heat fluxes between 5 and 175 W/cm² at varying time intervals. The specimen temperature is recorded on the front and backside as well as at different laminate depths. The CFRP is non-destructively tested with ultrasonic testing, infrared spectroscopy (ATR-FTIR), scanning electron microscopy (SEM), and micro-focused computed X-Ray tomography (μCT). Destructive tests are performed to evaluate the mechanical properties in terms of interlaminar shear strength (ILSS), compressive and tensile strength. The irradiation scenarios vary significantly in heat flux and exposure time. Thus, different heating rates, radiation effects, and temperature distributions occur. This leads to unequal decomposition processes, which affect the sensitivity of the strength type and damage behaviour of the specimens. However, with the use of surface coatings, thermal degradation of composite materials can be delayed.

Keywords: CFRP, one-sided thermal damage, high heat flux, heating rate, non-destructive and destructive testing

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Authors: Merry Meryam Martgrita, Marselina Irasonia Tan

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One of several aggresive cancer is cancer that overexpress c-erbB2 receptor along with the expression of estrogen receptor. Components of extracellular matrix play an important role to increase cancer cells proliferation, migration and invasion. Both components can affect cancer development by regulating the signal transduction pathways in cancer cells. In recent research, SKOV-3 ovarian cancer cell line, that overexpress c-erbB2 receptor was cultured on type IV collagen and treated with estradiol-17β, to reveal the role of both components on RNA and protein level of c-erbB2 receptor. In this research we found a modulation phenomena of increasing and decreasing of c-erbB2 RNA level and a stabilisation phenomena of c-erbB2 protein expression due to estradiol-17β and type IV collagen. It seemed that estradiol-17β has an important role to increase c-erbB2 transcription and the stability of c-erbB2 protein expression. Type IV collagen has an opposite role. It blocked c-erbB2 transcription when it bound to integrin receptor in SKOV-3 cells.

Keywords: c-erbB2, estradiol-17β, SKOV-3, type IV collagen

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Authors: Qingqing Gai, Junxing Shen, Yu Luo

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Due to the hardware architecture characteristics, some operators tend to acquire better performance if the input/output tensor dimensions are aligned to a certain minimum granularity, such as convolution and deconvolution commonly used in deep learning. Furthermore, if the requirements are not met, the general strategy is to pad with 0 to satisfy the requirements, potentially leading to the under-utilization of the hardware resources. Therefore, for the convolution and deconvolution whose input and output channels do not meet the minimum granularity alignment, we propose to transfer the W-dimensional data to the C-dimension for computation (W2C) to enable the C-dimension to meet the hardware requirements. This scheme also reduces the number of computations in the W-dimension. Although this scheme substantially increases computation, the operator’s speed can improve significantly. It achieves remarkable speedups on multiple hardware accelerators, including Nvidia Tensor cores, Qualcomm digital signal processors (DSPs), and Huawei neural processing units (NPUs). All you need to do is modify the network structure and rearrange the operator weights offline without retraining. At the same time, for some operators, such as the Reducemax, we observe that transferring the Cdimensional data to the W-dimension(C2W) and replacing the Reducemax with the Maxpool can accomplish acceleration under certain circumstances.

Keywords: convolution, deconvolution, W2C, C2W, alignment, hardware accelerator

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Authors: Logaiswari Indiran, Zainab Khalifah, Kamariah Ismail

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Business incubators have now been recognized as effective tools in providing business assistance to start-up firms. In both developed and developing countries, the number of incubators is growing tremendously. As the birth rate of incubators increases, so do its challenges. Malaysia, as one of the developing countries in the Asian continent, has also established a number of business incubators to breed and foster the growth and survival of start-up firms. Thus, this study discusses the incubation model applied in Malaysia and the challenges faced by these incubators using secondary data including policies, previous literature, and reports related to Malaysian incubators. The findings of this study call the government to rethink the key role of incubator managers and staffs, internal structure of the incubator concept and process, intellectual properties management, strategic alliances with universities-industries and funding supports in enhancing the support provided by the business incubators in Malaysia. The key challenges highlighted in this study signal important policy lessons for other developing countries that aim to create and map an effective business incubator ecosystem.

Keywords: business incubators, incubation challenges, funding support, incubator managers, internal structure, start-up firms

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Authors: U. Datta

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The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection

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Authors: Ambalika Ekka

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In today’s world, the growing demand for urban built forms has resulted in the production and consumption of building materials i.e. embodied energy in building construction, leading to pollution and greenhouse gas (GHG) emissions. Therefore, new buildings will offer a unique opportunity to implement more energy efficient building without compromising on building performance of the building. Embodied energy of building materials forms major contribution to embodied energy in buildings. The paper results in an approach towards designing an energy efficient apartment building through embodied energy assessment. This paper discusses the trend of residential development in Rourkela, which includes three case studies of the contemporary houses, followed by architectural elements, number of storeys, predominant material use and plot sizes using primary data. It results in identification of predominant material used and other characteristics in urban area. Further, the embodied energy coefficients of various dominant building materials and alternative materials manufactured in Indian Industry is taken in consideration from secondary source i.e. literature study. The paper analyses the embodied energy by estimating materials and operational energy of proposed building followed by altering the specifications of the materials based on the building components i.e. walls, flooring, windows, insulation and roof through res build India software and comparison of different options is assessed with consideration of sustainable parameters. This paper results that autoclaved aerated concrete block only reaches the energy performance Index benchmark i.e. 69.35 kWh/m² yr i.e. by saving 4% of operational energy and as embodied energy has no particular index, out of all materials it has the highest EE 23206202.43  MJ.

Keywords: energy efficient, embodied energy, EPI, building materials

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Authors: Patikineti Sreenivasulu, K. srinivasa Rao, A. Vinaya Babu

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The demand for portability, performance and high functional integration density of digital devices leads to the scaling of complementary metal oxide semiconductor (CMOS) devices inevitable. The increase in power consumption, coupled with the increasing demand for portable/hand-held electronics, has made power consumption a dominant concern in the design of VLSI circuits today. MTCMOS technology provides low leakage and high performance operation by utilizing high speed, low Vt (LVT) transistors for logic cells and low leakage, high Vt (HVT) devices as sleep transistors. Sleep transistors disconnect logic cells from the supply and/or ground to reduce the leakage in the sleep mode. In this technology, energy consumption while doing the mode transition and minimum time required to turn ON the circuit upon receiving the wake up signal are issues to be considered because these can adversely impact the performance of VLSI circuit. In this paper we are introducing an enhancing method of MTCMOS technology to optimize the power in MTCMOS sequential circuits.

Keywords: power consumption, ultra-low power, leakage, sub threshold, MTCMOS

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Authors: Chi-Chang Lin, Jiun-Yan Chiu

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Periodontal disease, oral cancer relating trauma is the prominent factor devastating bone tissue that is crucial to reestablishing in clinical. As we know, common symptom, osteoporosis, and infection limiting the ability of the bone tissue to recover cause difficulty before implantation therapy. Regeneration of bone tissue is the fundamental therapy before surgical processes. To promote the growth of bone tissue, many commercial products still have sophisticated problems that need to overcome. Regrettably, there is no available material which is apparently preferable for releasing and controlling of loading dosage, or mitigating inflammation. In our study, a hydrogel-based composite membrane has been prepared by using Gellan gum (GG), gamma-polyglutamic acid (γ-PGA) and glycerol with simple sol-gel method. GG is a natural material that is massively adopted in cartilage. Unfortunately, the strength of pure GG film is a manifest weakness especially under simulating body fluidic conditions. We utilize another biocompatible material, γ-PGA as cross-linker which can form tri-dimension structure that enhancing the strength. Our result indicated the strength of pure GG membrane can be obviously improved by cross-linked with γ-PGA (0.5, 0.6, 0.7, 0.8, 0.9, 1.0 w/v%). Besides, blending with glycerol (0, 1.0, 2.0, 3.0 w/v%) can significantly improve membrane toughness that corresponds to practical use. The innovative composited hydrogel made of GG, γ-PGA, and glycerol is attested with neat results including elongation and biocompatibility that take the advantage of extension covering major trauma. Recommendations are made for treatment to build up the foundation of bone tissue that would help patients to escape from the suffering and shorten the amount of time in recovery.

Keywords: bone tissue, gellan gum, regeneration, toughness

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Authors: Paul Hernandez-Herrera, Fernando Montoya, Juan Manuel Rendon, Alberto Darszon, Gabriel Corkidi

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Intracellular calcium ([Ca2+]i) regulates sperm motility. The analysis of [Ca2+]i has been traditionally achieved in two dimensions while the real movement of the cell takes place in three spatial dimensions. Due to optical limitations (high speed cell movement and low light emission) important data concerning the three dimensional movement of these flagellated cells had been neglected. Visualizing [Ca2+]i in 3D is not a simple matter since it requires complex fluorescence microscopy techniques where the resulting images have very low intensity and consequently low SNR (Signal to Noise Ratio). In 4D sequences, this problem is magnified since the flagellum oscillates (for human sperm) at least at an average frequency of 15 Hz. In this paper, a novel approach to extract the flagellum’s center-line in 4D stacks is presented. For this purpose, an iterative algorithm based on the fast-marching method is proposed to extract the flagellum’s center-line. Quantitative and qualitative results are presented in a 4D stack to demonstrate the ability of the proposed algorithm to trace the flagellum’s center-line. The method reached a precision and recall of 0.96 as compared with a semi-manual method.

Keywords: flagellum, minimal path, segmentation, sperm

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Authors: M. Khairudin

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This paper investigates the system identification and design quantitative feedback theory (QFT) for the robust control of a lathe spindle. The dynamic of the lathe spindle is uncertain and time variation due to the deepness variation on cutting process. System identification was used to obtain the dynamics model of the lathe spindle. In this work, real time system identification is used to construct a linear model of the system from the nonlinear system. These linear models and its uncertainty bound can then be used for controller synthesis. The real time nonlinear system identification process to obtain a set of linear models of the lathe spindle that represents the operating ranges of the dynamic system. With a selected input signal, the data of output and response is acquired and nonlinear system identification is performed using Matlab to obtain a linear model of the system. Practical design steps are presented in which the QFT-based conditions are formulated to obtain a compensator and pre-filter to control the lathe spindle. The performances of the proposed controller are evaluated in terms of velocity responses of the the lathe machine spindle in corporating deepness on cutting process.

Keywords: lathe spindle, QFT, robust control, system identification

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Authors: Katsuyuki Umezawa, Makoto Nakazawa, Manabu Kobayashi, Yutaka Ishii, Michiko Nakano, Shigeichi Hirasawa

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This research aims to develop a self-study system equipped with an artificial teacher who gives advice to students by detecting the learners and to evaluate language learning in a unified framework. 'Detecting the learners' means that the system understands the learners' learning conditions, such as each learner’s degree of understanding, the difference in each learner’s thinking process, the degree of concentration or boredom in learning, and problem solving for each learner, which can be interpreted from learning behavior. In this paper, we propose a system to efficiently collect brain waves from learners by focusing on only the brain waves among the biological information for 'detecting the learners'. The conventional Electroencephalograph (EEG) measurement method during learning using a simple EEG has the following disadvantages. (1) The start and end of EEG measurement must be done manually by the experiment participant or staff. (2) Even when the EEG signal is weak, it may not be noticed, and the data may not be obtained. (3) Since the acquired EEG data is stored in each PC, there is a possibility that the time of data acquisition will be different in each PC. This time, we developed a system to collect brain wave data on the server side. This system overcame the above disadvantages.

Keywords: artificial teacher, e-learning, self-study system, simple EEG

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Authors: Arpan Bera, Rini Ganguly, Raja Chakraborty, Amlan J. Pal

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To deal with the increasing demands for the high-density non-volatile memory devices, we need nano-sites with efficient and stable charge storage capabilities. We prepared nanocrystals (NCs) of inorganic perovskite, CsPbCl₃ coated with Cs₄PbCl₆, by colloidal synthesis. Due to the type-I band alignment at the junction, this core-shell composite is expected to behave as a charge trapping site. Using Scanning Tunneling Spectroscopy (STS), we investigated voltage-controlled resistive switching in this heterostructure by tracking the change in its current-voltage (I-V) characteristics. By applying voltage pulse of appropriate magnitude on the NCs through this non-invasive method, different resistive states of this system were systematically accessed. For suitable pulse-magnitude, the response jumped to a branch with enhanced current indicating a high-resistance state (HRS) to low-resistance state (LRS) switching in the core-shell NCs. We could reverse this process by using a pulse of opposite polarity. These two distinct resistive states can be considered as two logic states, 0 and 1, which are accessible by varying voltage magnitude and polarity. STS being a local probe in space enabled us to capture this switching at individual NC site. Hence, we claim a bright prospect of these core-shell NCs made of inorganic halide perovskites in future high density memory application.

Keywords: Core-shell perovskite, CsPbCl₃-Cs₄PbCl₆, resistive switching, Scanning Tunneling Spectroscopy

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Authors: Yogesh Mahor, Subhash Nigam, Abhai Khare

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Road safety education is a composite subject which should be viewed holistically if taken into accoubehavior change communication, safe road infrastructure and low enforcement. Specific and customized road safety education is crucial for each type of road user and learners in the formal and informal teaching and various kind of training programs directly sponsored by state and center government, as they are active contributors to shaping a community and responsible citizens. The aim of this discussion article is to explore a strategy to integrate road safety education into the formal curriculum of schools, higher education institutions, driving schools, skill development centers, various government funded urban and rural development training institutions and their work plans as standing agenda. By applying the desktop research method, the article conceptualizes what the possible focus of road safety education and training should be. The article then explores international common practices in road safety education and training, and considers the necessary synergy between education, road engineering and low enforcement. The article uses secondary data collected from documents which are then analysed in a sectoral way. A well-designed road safety strategy for mainstreaming education and government-sponsored training is urgently needed, facilitating partnerships in various sectors to implement such education in the students and learners in multidisciplinary ways.

Keywords: road safety education, curriculum-based road safety education, behavior change communication, low enforcement, road engineering, safe system approach, infrastructure development consultants

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Authors: M. Iruleswari, A. Jeyapaul Murugan

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Most fundamental part used in many Digital Signal Processing (DSP) application is a Finite Impulse Response (FIR) filter because of its linear phase, stability and regular structure. Designing a high-speed and hardware efficient FIR filter is a very challenging task as the complexity increases with the filter order. In most applications the higher order filters are required but the memory usage of the filter increases exponentially with the order of the filter. Using multipliers occupy a large chip area and need high computation time. Multiplier-less memory-based techniques have gained popularity over past two decades due to their high throughput processing capability and reduced dynamic power consumption. This paper describes the design and implementation of highly efficient Look-Up Table (LUT) based circuit for the implementation of FIR filter using Distributed arithmetic algorithm. It is a multiplier less FIR filter. The LUT can be subdivided into a number of LUT to reduce the memory usage of the LUT for higher order filter. Analysis on the performance of various filter orders with different address length is done using Xilinx 14.5 synthesis tool. The proposed design provides less latency, less memory usage and high throughput.

Keywords: finite impulse response, distributed arithmetic, field programmable gate array, look-up table

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Authors: Ling Qi, Matloob Khushi, Josiah Poon

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This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.

Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning

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Authors: G. C. Tikkiwal, Mukesh Upadhyay

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During the surveillance operations at war or peace time, the Radar operator gets a scatter of targets over the screen. This may be a tracked vehicle like tank vis-à-vis T72, BMP etc, or it may be a wheeled vehicle like ALS, TATRA, 2.5Tonne, Shaktiman or moving army, moving convoys etc. The Radar operator selects one of the promising targets into Single Target Tracking (STT) mode. Once the target is locked, the operator gets a typical audible signal into his headphones. With reference to the gained experience and training over the time, the operator then identifies the random target. But this process is cumbersome and is solely dependent on the skills of the operator, thus may lead to misclassification of the object. In this paper we present a technique using mathematical and statistical methods like Fast Fourier Transformation (FFT) and Principal Component Analysis (PCA) to identify the random objects. The process of classification is based on transforming the audible signature of target into music octave-notes. The whole methodology is then automated by developing suitable software. This automation increases the efficiency of identification of the random target by reducing the chances of misclassification. This whole study is based on live data.

Keywords: radar target, fft, principal component analysis, eigenvector, octave-notes, dsp

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Authors: Lebogang L. R. Mphahlele, Bruce B. Sithole

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Chicken meat is the highest consumed meat in south Africa, with a per capita consumption of >33 kg yearly. Hence, South Africa produces over 250 million kg of waste chicken feathers each year, the majority of which is landfilled or incinerated. The discarded feathers have caused environmental pollution and natural protein resource waste. Therefore, the valorisation of waste chicken feathers is measured as a more environmentally friendly and cost-effective treatment. Feather contains 91% protein, the main component being beta-keratin, a fibrous and insoluble structural protein extensively cross linked by disulfide bonds. Keratin is usually converted it into nanofibers via electrospinning for a variety of applications. keratin nanofiber composites have many potential biomedical applications for their attractive features, such as high surface-to-volume ratio and very high porosity. The application of nanofibers in the biomedical wound dressing requires antimicrobial properties for materials. One approach is incorporating inorganic nanoparticles, among which silver nanoparticles played an important alternative antibacterial agent and have been studied against many types of microbes. The objective of this study is to combine synthetic polymer, chicken feather keratin, and antibacterial nanoparticles to develop novel electrospun antibacterial nanofibrous composites for possible wound dressing application. Furthermore, this study will converting a two-dimensional electrospun nanofiber membrane to three-dimensional fiber networks that resemble the structure of the extracellular matrix (ECM)

Keywords: chicken feather keratin, nanofibers, nanoparticles, nanocomposites, wound dressing

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Authors: Biji Jacob

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Vector quantization algorithm which uses minimum distance calculation for codebook generation, a time consuming calculation performed on each pixel values leads to computation complexity. The codebook is updated by comparing the distance of each vector to their centroid vector and measure for their closeness. In this paper vector quantization is modified based on vector difference algorithm for image enhancement purpose. In the proposed scheme, vector differences between the vectors are considered as the new generation vectors or new codebook vectors. The codebook is updated by comparing the new generation vector with a threshold value having minimum error with the parent vector. The minimum error decides the fitness of each newly generated vector. Thus the codebook is generated in an adaptive manner and the fitness value is determined for the suppression of the degraded portion of the image and thereby leads to the enhancement of the image through the adaptive searching capability of the vector quantization through vector difference algorithm. Experimental results shows that the vector difference scheme efficiently modifies the vector quantization algorithm for enhancing the image with peak signal to noise ratio (PSNR), mean square error (MSE), Euclidean distance (E_dist) as the performance parameters.

Keywords: codebook, image enhancement, vector difference, vector quantization

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Authors: Hua Cao, Laurent Peyrodie, Olivier Agnani, Cecile Donze

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Multiple sclerosis (MS) is a disease, which affects the central nervous system, and causes balance problem. In clinical, this disorder is usually evaluated using static posturography. Some linear or nonlinear measures, extracted from the posturographic data (i.e. center of pressure, COP) recorded during a balance test, has been used to analyze postural control of MS patients. In this study, the trend (TREND) and the sample entropy (SampEn), two nonlinear parameters were chosen to investigate their relationships with the expanded disability status scale (EDSS) score. Forty volunteers with different EDSS scores participated in our experiments with eyes open (EO) and closed (EC). TREND and two types of SampEn (SampEn1 and SampEn2) were calculated for each combined COP’s position signal. The results have shown that TREND had a weak negative correlation to EDSS while SampEn2 had a strong positive correlation to EDSS. Compared to TREND and SampEn1, SampEn2 showed a better significant correlation to EDSS and an ability to discriminate the MS patients in the EC case. In addition, the outcome of the study suggests that the multi-dimensional nonlinear analysis could provide some information about the impact of disability progression in MS on dynamics of the COP data.

Keywords: balance, multiple sclerosis, nonlinear analysis, postural sway

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Authors: Marin Senila, Oana Cadar, Thorsten Janisch, Patrick Lacroix-Desmazes

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The study presents the analytical capability and validation of a method based on microwave-assisted acid digestion for quantitative determination of platinum and palladium in catalysts using inductively coupled plasma optical emission spectrometry (ICP-OES). In order to validate the method, the main figures of merit such as limit of detection and limit of quantification, precision and accuracy were considered and the measurement uncertainty was estimated based on the bottom-up approach according to the international guidelines of ISO/IEC 17025. Limit of detections, estimated from blank signal using 3 s criterion, were 3.0 mg/kg for Pt and respectively 3.6 mg/kg for Pd, while limits of quantification were 9.0 mg/kg for Pt and respectively 10.8 mg/kg for Pd. Precisions, evaluated as standard deviations of repeatability (n=5 parallel samples), were less than 10% for both precious metals. Accuracies of the method, verified by recovery estimation certified reference material NIST SRM 2557 - pulverized recycled monolith, were 99.4 % for Pt and 101% for Pd. The obtained limit of quantifications and accuracy were satisfactory for the intended purpose. The paper offers all the steps necessary to validate the determination method for Pt and Pd in catalysts using inductively coupled plasma optical emission spectrometry.

Keywords: catalyst analysis, ICP-OES, method validation, platinum, palladium

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Authors: Weinian Wang, Joseph C. Chen

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The objective of this research is to optimize the process of cutting cylindrical workpieces utilizing live tooling on a HAAS ST-20 lathe. Surface roughness (Ra) has been investigated as the indicator of quality characteristics for machining process. Aluminum alloy was used to conduct experiments due to its wide range usages in engineering structures and components where light weight or corrosion resistance is required. In this study, Taguchi methodology is utilized to determine the effects that each of the parameters has on surface roughness (Ra). A total of 18 experiments of each process were designed according to Taguchi’s L9 orthogonal array (OA) with four control factors at three levels of each and signal-to-noise ratios (S/N) were computed with Smaller the better equation for minimizing the system. The optimal parameters identified for the surface roughness of the turning operation utilizing live tooling were a feed rate of 3 inches/min(A3); a spindle speed of 1300 rpm(B3); a 2-flute titanium nitrite coated 3/8” endmill (C1); and a depth of cut of 0.025 inches (D2). The mean surface roughness of the confirmation runs in turning operation was 8.22 micro inches. The final results demonstrate that Taguchi methodology is a sufficient way of process improvement in turning process on surface roughness.

Keywords: CNC milling operation, CNC turning operation, surface roughness, Taguchi parameter design

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Authors: Saja M. Nabat Al-Ajrash, Charles Browning, Rose Eckerle, Li Cao

Abstract:

Three preceramic polymer formulations for potential use in 3D printing technologies were investigated. The polymeric precursors include an allyl hydrido polycarbosilane (SMP-10), SMP-10/1,6-dexanediol diacrylate (HDDA) mixture, and polydimethylsiloxane (PDMS). The rheological property of the polymeric precursors, including the viscosity within a wide shear rate range was compared to determine the applicability in additive manufacturing technology. The structural properties of the polymeric solutions and their photocureability were investigated using Fourier transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC). Moreover, thermogravimetric analysis (TGA) and X-ray diffraction (XRD) were utilized to study polymeric to ceramic conversion for versatile precursors. The prepared precursor resin proved to have outstanding photo-curing properties and the ability to transform to the silicon carbide phase at temperatures as low as 850 °C. The obtained ceramic was fully dense with nearly linear shrinkage and a shiny, smooth surface after pyrolysis. Furthermore, after pyrolysis to 1350 °C and TGA analysis, PDMS polymer showed the highest onset decomposition temperature and the lowest retained weight (52 wt%), while SMP.10/HDDA showed the lowest onset temperature and ceramic yield (71.7 wt%). In terms of crystallography, the ceramic matrix composite appeared to have three coexisting phases, including silicon carbide, and silicon oxycarbide. The results are very promising to fabricate ceramic materials working at high temperatures with complex geometries.

Keywords: preceramic polymer, silicon carbide, photocuring, allyl hydrido polycarbosilane, SMP-10

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Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas

Abstract:

This paper presents a comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in the speaker-dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signals to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients give best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose, the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfies the real-time requirements and is suitable for applications in embedded systems.

Keywords: isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW

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Authors: Yan Liu

Abstract:

The Gini coefficient indicates that the inequality of income distribution is rising in China. How individuals viewing the equality of current society is an important predicator of social turbulence. Perceptions of social justice may vary according to the social stratification. People usually use socioeconomic status to identify divisions between social stratifications. The objective of this study is to explore the potential influence of socioeconomic status on citizens’ perceptions of social justice in China. Socioeconomic status (SES) is usually reflected by either an SES indicator or a composite of three core dimensions: education, income and occupation. With data collected in the 2010 Chinese General Social Survey (CGSS), this study uses OLS regression analyses to examine the relationship between socioeconomic status (SES) and citizens’ perceptions of social justice. This study finds that most Chinese citizens believe that the current society is fair or more than fair. Socioeconomic status (SES) has a positive impact on citizens’ perceptions of social justice, which means individuals with higher indicator of socioeconomic status prefer to believe current society is fair. However, the three core dimensions which are used to measure socioeconomic status (SES) have different influences on perceptions of social justice: First, income helps enhance citizens’ sense of social justice. Second, education weakens citizens’ sense of social justice. Third, compared to the middle occupational status, people of both higher occupational status and lower occupational status have higher levels of perceptions of social justice. Though education creates a negative influence on perceptions of social justice, its effect is much weaker than that of income, which indicates income is a determining factor for enhancing people’s perceptions of social justice in China’s market society. Policy implications are discussed.

Keywords: education, income, occupation, perceptions of social justice, social stratification, socioeconomic status

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Authors: Ricardo Mendoza, Jason Briceño, Juan F. Santa, Gabriel Peluffo, Mauricio Márquez, Beatriz Cardozo, Carlos Gutiérrez

Abstract:

The most common controlled method to obtain impact strength of composites materials is performing a Charpy Impact Test which consists of a pendulum with calibrated mass and length released from a known height. In fact, composites components experience impact events in normal operations such as when a tool drops or a foreign object strikes it. These events are categorized into low velocity impact (LVI) which typically occurs at velocities below 10m/s. In this study, the major aim was to calculate the absorbed energy during the impact. Tests were performed on three types of composite panels: fiberglass laminated panels, coir fiber reinforced polyester and coir fiber reinforced polyester subjected to water immersion for 48 hours. Coir fibers were obtained in local plantations of the Caribbean coast of Colombia. They were alkali treated in 5% aqueous NaOH solution for 2h periods. Three type of shape impactors were used on drop-weight impact test including hemispherical, ogive and pointed. Failure mechanisms and failure modes of specimens were examined using an optical microscope. Results demonstrate a reduction in absorbed energy correlated with the increment of water absorption of the panels. For each level of absorbed energy, it was possible to associate a different fracture state. This study compares results of energy absorbed obtained from two impact test methods.

Keywords: coir fiber, polyester composites, low velocity impact, Charpy impact test, drop-weight impact test

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Authors: Ye Ling, Ruan Haihui

Abstract:

Aqueous Zn-ion hybrid supercapacitors (AZHSCs) pertain to a new type of electrochemical energy storage device that has received considerable attention. They integrate the advantages of high-energy Zn-ion batteries and high-power supercapacitors to meet the demand for low-cost, long-term durability, and high safety. Nevertheless, the challenge caused by the finite ion adsorption/desorption capacity of carbon electrodes gravely limits their energy densities. This work describes titanium nitride@nitrogen-doped carbon nanocage (TiN@NCNC) composite cathodes for AZHSCs to achieve a greatly improved energy density, and the composites can be facile synthesized based on the calcination of a mixture of tetrabutyl titanate and zeolitic imidazolate framework-8 in argon atmosphere. The resulting composites are featured by the ultra-fine TiN particles dispersed uniformly on the NCNC surfaces, enhancing the Zn2+ storage capabilities. Using TiN@NCNC cathodes, the AZHSCs can operate stably with a high energy density of 154 Wh kg-¹ at a specific power of 270 W kg-¹ and achieve a remarkable capacity retention of 88.9% after 104 cycles at 5 A g-¹. At an extreme specific power of 8.7 kW kg-1, the AZHSCs can retain an energy density of 97.2 Wh kg-1. With these results, we stress that the TiN@NCNC cathodes render high-performance AZHSCs, and the facile one-pot method can easily be scaled up, which enables AZHSCs a new energy-storage component for managing intermitted renewable energy sources.

Keywords: Zn-ion hybrid supercapacitors, ion absorption/desorption reactions, titanium nitride, zeolitic imidazolate framework-8

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