Search results for: array signal processing

Authors: Qiaoyun Yang

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Organizational scholars have paid enormous attention on how local governments manage their knowledge during the past two decades. Government knowledge management (KM) research recognizes that the management of knowledge flows and networks is critical to reforms on government service efficiency and the effect of administration. When dealing with complex affairs, all the limitations resulting from a lack of KM concept, processes and technologies among all the involved organizations begin to be exposed and further compound the processing difficulty of the affair. As a result, the challenges for individual or group knowledge sharing, knowledge digging and organizations’ collaboration in government's activities are diverse and immense. This analysis presents recent situation of government KM in China drawing from a total of more than 300 questionnaires and highlights important challenges that remain. The causes of the lapses in KM processes within and across the government agencies are discussed.

Keywords: KM processes, KM technologies, government, KM situation

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Authors: Dev Pratap Singh, Harshika Hasija, Ashwini S.

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The project aims to provide a touchless, intuitive interface for human-computer interaction, enabling users to control their computers using hand gestures and voice commands. The system leverages advanced computer vision techniques using the Media Pipe framework and OpenCV to detect and interpret real-time hand gestures, transforming them into mouse actions such as clicking, dragging, and scrolling. Additionally, the integration of a voice assistant powered by the speech recognition library allows for seamless execution of tasks like web searches, location navigation, and gesture control in the system through voice commands.

Keywords: gesture recognition, hand tracking, machine learning, convolutional neural networks, natural language processing, voice assistant

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Authors: John Hawkins, Graham Burton

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Contextual targeting is a common strategy for advertising that places marketing messages in media locations that are expected to be aligned with the target audience. There are multiple major challenges to contextual targeting: the ideal categorisation scheme needs to be known, as well as the most appropriate subsections of that scheme for a given campaign or creative. In addition, the campaign reach is typically limited when targeting becomes narrow, so a balance must be struck between requirements. Finally, refinement of the process is limited by the use of evaluation methods that are either rapid but non-specific (click through rates), or reliable but slow and costly (conversions or brand recall studies). In this study we evaluate the use of attention measurement as a technique for understanding the performance of targeting on the basis of specific contextual topics. We perform the analysis using a large scale dataset of impressions categorised using the iAB V2.0 taxonomy. We evaluate multiple levels of the categorisation hierarchy, using categories at different positions within an initial creative specific ranking. The results illustrate that measuring attention time is an affective signal for the performance of a specific creative within a specific context. Performance is sustained across a ranking of categories from one period to another.

Keywords: contextual targeting, digital advertising, attention measurement, marketing performance

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Authors: Tamara Romero, Manuel Romero-Huelva, Jose V. Segarra, Jose Castro, Carlos Fernandez

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Many foods resulting from processing and manufacturing end up as waste, most of which is burned, dumped into landfills or used as compost, which leads to wasted resources, and environmental problems due to unsuitable disposal. Using residues of the crop and food processing industries to feed livestock has the advantage to obviating the need for costly waste management programs. The main residue generated in citrus cultivations and rice crop are pruning waste and rice straw, respectively. Within Spain, the Valencian Community is one of the world's oldest citrus and rice production areas. The objective of this experiment found out the effects of including orange leaves and rice straw as ingredients in the concentrate diets of goats, on milk production and methane (CH₄) emissions. Ten Murciano-Granadina dairy goats (45 kg of body weight, on average) in mid-lactation were selected in a crossover design experiment, where each goat received two treatments in 2 periods. Both groups were fed with 1.7 kg pelleted mixed ration; one group (n= 5) was a control (C) and the other group (n= 5) used orange leaves and rice straw (OR). The forage was alfalfa hay, and it was the same for the two groups (1 kg of alfalfa was offered by goat and day). The diets employed to achieve the requirements during lactation period for caprine livestock. The goats were allocated to individual metabolism cages. After 14 days of adaptation, feed intake and milk yield were recorded daily over a 5 days period. Physico-chemical parameters and somatic cell count in milk samples were determined. Then, gas exchange measurements were recorded individually by an open-circuit indirect calorimetry system using a head box. The data were analyzed by mixed model with diet and digestibility as fixed effect and goat as random effect. No differences were found for dry matter intake (2.23 kg/d, on average). Higher milk yield was found for C diet than OR (2.3 vs. 2.1 kg/goat and day, respectively) and, greater milk fat content was observed for OR than C (6.5 vs. 5.5%, respectively). The cheese extract was also greater in OR than C (10.7 vs. 9.6%). Goats fed OR diet produced significantly fewer CH₄ emissions than C diet (27 vs. 30 g/d, respectively). These preliminary results (LIFE Project LOWCARBON FEED LIFE/CCM/ES/000088) suggested that the use of these waste by-products was effective in reducing CH₄ emission without detrimental effect on milk yield.

Keywords: agricultural waste, goat, milk production, methane emission

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Authors: Tayab D. Memon, Shahji Farooque, Marvi Deshi, Imtiaz Hussain Kalwar, B. S. Chowdhry

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Recently single-bit ternary FIR-like filter (SBTFF) hardware synthesize in FPGA is reported and compared with multi-bit FIR filter on similar spectral characteristics. Results shows that SBTFF dominates upon multi-bit filter overall. In this paper, an optimized adder module for ternary quantized sigma-delta modulated signal is presented. The adder is simulated using ModelSim for functional verification the area-performance of the proposed adder were obtained through synthesis in Xilinx and compared to conventional adder trees. The synthesis results show that the proposed adder tree achieves higher clock rates and lower chip area at higher inputs to the adder block; whereas conventional adder tree achieves better performance and lower chip area at lower number of inputs to the same adder block. These results enhance the usefulness of existing short word length DSP algorithms for fast and efficient mobile communication.

Keywords: short word length (SWL), DSP algorithms, FPGA, SBTFF, VHDL

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Authors: Punnoose A. K.

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This paper presents an approach for identifying noisy speech recording using a multi-layer perception (MLP) trained to predict phonemes from acoustic features. Characteristics of the MLP posteriors are explored for clean speech and noisy speech at the frame level. Appropriate density functions are used to fit the softmax probability of the clean and noisy speech. A function that takes into account the ratio of the softmax probability density of noisy speech to clean speech is formulated. These phoneme independent scoring is weighted using a phoneme-specific weightage to make the scoring more robust. Simple thresholding is used to identify the noisy speech recording from the clean speech recordings. The approach is benchmarked on standard databases, with a focus on precision.

Keywords: noisy speech identification, speech pre-processing, noise robustness, feature engineering

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Authors: N. David, H. O. Gao

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Air pollution is a serious environmental threat on a global scale and can cause harm to human health, morbidity and premature mortality. Reliable monitoring and control systems are therefore necessary to develop coping skills against the hazards associated with this phenomenon. However, existing environmental monitoring means often do not provide a sufficient response due to practical and technical limitations. Commercial microwave links that form the infrastructure for transmitting data between cell phone towers can be harnessed to map rain at high tempo-spatial resolution. Rainfall causes a decrease in the signal strength received by these wireless communication links allowing it to be used as a built-in sensor network to map the phenomenon. In this study, we point to the potential that lies in this system to indirectly monitor areas where air pollution is reduced. The relationship between pollutant wash-off and rainfall provides an opportunity to acquire important spatial information about air quality using existing cell-phone tower signals. Since the density of microwave communication networks is high relative to any dedicated sensor arrays, it could be possible to rely on this available observation tool for studying precipitation scavenging on air pollutants, for model needs and more.

Keywords: air pollution, commercial microwave links, rainfall, washout

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Authors: Sajjad Esmaeili, Robert Krause, Lukas Gerlich, Alireza Mohammadian Kia, Benjamin Uhlig

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This investigation aims to develop the feasible and qualitative process parameters for the thin films fabrication into ultra-large through-silicon-vias (TSVs) as vertical interconnections. The focus of the study is on TSV metallization and its challenges employing new materials for the purpose of rapid signal propagation in the microsystems technology. Cobalt metal-organic chemical vapor deposition (Co-MOCVD) process enables manufacturing an adhesive and excellent conformal ultra-thin film all the way through TSVs in comparison with the conventional non-conformal physical vapor deposition (PVD) process of copper (Cu) seed layer. Therefore, this process provides a Cu seed-free layer which is capable of direct Cu electrochemical deposition (Cu-ECD) on top of it. The main challenge of this metallization module is to achieve the proper alternative seed layer with less roughness, sheet resistance and granular organic contamination (e.g. carbon) which intensify the Co corrosion under the influence of Cu electrolyte.

Keywords: Cobalt MOCVD, direct Cu electrochemical deposition (ECD), metallization technology, through-silicon-via (TSV)

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Authors: Peng Cheng, Liqing Wei, Hongyu Chen, Ruomiao Wang

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This paper discusses a light-weight reinforced thermoplastic (LWRT) composite with superior fire retardancy. This porous LWRT composite is manufactured using polyolefin, fiberglass, and fire retardant additives via a wet-lay process. However, discoloration of the LWRT can be induced by various mechanisms, which may be a concern in the building and construction industry. It is commonly understood that discoloration is strongly associated with the presence of phenolic antioxidant(s) and NO_x. The over-oxidation of phenolic antioxidant(s) is probably the root-cause of the discoloration (pinking/yellowing). Hanwha Azdel, Inc. developed a LWRT with fire-retardant property of ASTM E84-Class A specification, as well as negligible discoloration even under harsh conditions. In addition, this thermoplastic material is suitable for secondary processing (e.g. compression molding) if necessary.

Keywords: discoloration, fire-retardant, thermoplastic composites, wet-lay process

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Authors: Chusak Thanawattano, Roongroj Bhidayasiri

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This paper proposes a novel feature set utilized for classifying the Parkinson tremor and essential tremor. Ten ET and ten PD subjects are asked to perform kinetic, postural and resting tests. The empirical mode decomposition (EMD) is used to decompose collected tremor signal to a set of intrinsic mode functions (IMF). The IMFs are used for reconstructing representative signals. The feature set is composed of peak frequencies of IMFs and reconstructed signals. Hypothesize that the dominant frequency components of subjects with PD and ET change in different directions for different tests, difference of peak frequencies of IMFs and reconstructed signals of pairwise based tests (kinetic-resting, kinetic-postural and postural-resting) are considered as potential features. Sets of features are used to train and test by classifier including the quadratic discriminant classifier (QLC) and the support vector machine (SVM). The best accuracy, the best sensitivity and the best specificity are 90%, 87.5%, and 92.86%, respectively.

Keywords: tremor, Parkinson, essential tremor, empirical mode decomposition, quadratic discriminant, support vector machine, peak frequency, auto-regressive, spectrum estimation

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Authors: G. Zakharov, Z. Aslamazashvili, M. Chikhradze, D. Kvaskhvadze, N. Khidasheli, S. Gvazava

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Traditional technologies for processing iron-containing industrial waste, including steel-rolling production, are associated with significant energy costs, the long duration of processes, and the need to use complex and expensive equipment. Waste generated during the industrial process negatively affects the environment, but at the same time, it is a valuable raw material and can be used to produce new marketable products. The study of the effectiveness of self-propagating high-temperature synthesis (SHS) methods, which are characterized by the simplicity of the necessary equipment, the purity of the final product, and the high processing speed, is under the wide scientific and practical interest to solve the set problem. The work presents technological aspects of the production of Ferro boron by the method of SHS - metallurgy from iron-containing wastes of rolled production for alloying of cast iron and results of the effect of alloying element on the degree of boron assimilation with liquid cast iron. Features of Fe-B system combustion have been investigated, and the main parameters to control the phase composition of synthesis products have been experimentally established. Effect of overloads on patterns of cast ligatures formation and mechanisms structure formation of SHS products was studied. It has been shown that an increase in the content of hematite Fe₂O₃ in iron-containing waste leads to an increase in the content of phase FeB and, accordingly, the amount of boron in the ligature. Boron content in ligature is within 3-14%, and the phase composition of obtained ligatures consists of Fe₂B and FeB phases. Depending on the initial composition of the wastes, the yield of the end product reaches 91 - 94%, and the extraction of boron is 70 - 88%. Combustion processes of high exothermic mixtures allow to obtain a wide range of boron-containing ligatures from industrial wastes. In view of the relatively low melting point of the obtained SHS-ligature, the positive dynamics of boron absorption by liquid iron is established. According to the obtained data, the degree of absorption of the ligature by alloying gray cast iron at 1450°C is 80-85%. When combined with the treatment of liquid cast iron with magnesium, followed by alloying with the developed ligature, boron losses are reduced by 5-7%. At that, uniform distribution of boron micro-additives in the volume of treated liquid metal is provided. Acknowledgment: This work was supported by Shota Rustaveli Georgian National Science Foundation of Georgia (SRGNSFG) under the GENIE project (grant number № CARYS-19-802).

Keywords: self-propagating high-temperature synthesis, cast iron, industrial waste, ductile iron, structure formation

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Authors: Nattapong Techarattanased

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This research paper aimed to identify determinants of airline service quality on passengers’ repeated purchase of service. The population of this study was Thai passengers flying domestic flights with Thai Airways, making a total of 300 samples. These 300 samples participated in this research by answering a collection of questions by means of a questionnaire. An analysis of means score and multiple regression revealed that perceived service quality for tangible elements, reliability, responsiveness, assurance and empathy had determined repeated purchase of flight service of the passengers at a high level. Moreover, reliability and responsiveness factors could predict the passengers’ repeated purchase of flight service at the percentage of 30.6. The findings gave a signal that Thai Airways may consider a development of route network and fleet strategy as well as an establishment of aircraft and seat qualification to meet passengers’ needs and requirements. Passengers’ level of satisfaction could also be maximized by offering service value through various kinds of special deals and programs, whereas value- added pricing strategy should be considered in order to differentiate from and beat other leading airline competitors.

Keywords: repeated purchase, service quality, domestic flight, Thai Airways

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Authors: Saleh Gorji, Sahil Gulati, Ana Pakzad

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Continuous electron diffraction tomography, also known as microcrystal electron diffraction (MicroED) or three-dimensional electron diffraction (3DED), is a powerful technique, which in combination with cryo-electron microscopy (cryo-ED), can provide atomic-scale 3D information about the crystal structure and composition of different classes of crystalline materials such as proteins, peptides, and small molecules. Unlike the well-established X-ray crystallography method, 3DED does not require large single crystals and can collect accurate electron diffraction data from crystals as small as 50 – 100 nm. This is a critical advantage as growing larger crystals, as required by X-ray crystallography methods, is often very difficult, time-consuming, and expensive. In most cases, specimens studied via 3DED method are electron beam sensitive, which means there is a limitation on the maximum amount of electron dose one can use to collect the required data for a high-resolution structure determination. Therefore, collecting data using a conventional scintillator-based fiber coupled camera brings additional challenges. This is because of the inherent noise introduced during the electron-to-photon conversion in the scintillator and transfer of light via the fibers to the sensor, which results in a poor signal-to-noise ratio and requires a relatively higher and commonly specimen-damaging electron dose rates, especially for protein crystals. As in other cryo-EM techniques, damage to the specimen can be mitigated if a direct detection camera is used which provides a high signal-to-noise ratio at low electron doses. In this work, we have used two classes of such detectors from Gatan, namely the K3® camera (a monolithic active pixel sensor) and Stela™ (that utilizes DECTRIS hybrid-pixel technology), to address this problem. The K3 is an electron counting detector optimized for low-dose applications (like structural biology cryo-EM), and Stela is also a counting electron detector but optimized for diffraction applications with high speed and high dynamic range. Lastly, data collection workflows, including crystal screening, microscope optics setup (for imaging and diffraction), stage height adjustment at each crystal position, and tomogram acquisition, can be one of the other challenges of the 3DED technique. Traditionally this has been all done manually or in a partly automated fashion using open-source software and scripting, requiring long hours on the microscope (extra cost) and extensive user interaction with the system. We have recently introduced Latitude® D in DigitalMicrograph® software, which is compatible with all pre- and post-energy-filter Gatan cameras and enables 3DED data acquisition in an automated and optimized fashion. Higher quality 3DED data enables structure determination with higher confidence, while automated workflows allow these to be completed considerably faster than before. Using multiple examples, this work will demonstrate how to direct detection electron counting cameras enhance 3DED results (3 to better than 1 Angstrom) for protein and small molecule structure determination. We will also show how Latitude D software facilitates collecting such data in an integrated and fully automated user interface.

Keywords: continuous electron diffraction tomography, direct detection, diffraction, Latitude D, Digitalmicrograph, proteins, small molecules

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Authors: Bartlomiej S. Witkowski, Lukasz Wachnicki, Sylwia Gieraltowska, Rafal Pietruszka, Marek Godlewski

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Zinc oxide is extensively studied II-VI semiconductor with a direct energy gap of about 3.37 eV at room temperature and high transparency in visible light spectral region. Due to these properties, ZnO is an attractive material for applications in photovoltaic, electronic and optoelectronic devices. ZnO nanorods, due to a well-developed surface, have potential of applications in sensor technology and photovoltaics. In this work we present a new inexpensive method of the ultra-fast growth of ZnO nanorods from the aqueous solution. This environment friendly and fully reproducible method allows growth of nanorods in few minutes time on various substrates, without any catalyst or complexing agent. Growth temperature does not exceed 50ºC and growth can be performed at atmospheric pressure. The method is characterized by simplicity and allows regulation of size of the ZnO nanorods in a large extent. Moreover the method is also very safe, it requires organic, non-toxic and low-price precursors. The growth can be performed on almost any type of substrate through the homo-nucleation as well as hetero-nucleation. Moreover, received nanorods are characterized by a very high quality - they are monocrystalline as confirmed by XRD and transmission electron microscopy. Importantly oxygen vacancies are not found in the photoluminescence measurements. First results for obtained by us ZnO nanorods in sensor applications are very promising. Resistance UV sensor, based on ZnO nanorods grown on a quartz substrates shows high sensitivity of 20 mW/m2 (2 μW/cm2) for point contacts, especially that the results are obtained for the nanorods array, not for a single nanorod. UV light (below 400 nm of wavelength) generates electron-hole pairs, which results in a removal from the surfaces of the water vapor and hydroxyl groups. This reduces the depletion layer in nanorods, and thus lowers the resistance of the structure. The so-obtained sensor works at room temperature and does not need the annealing to reset to initial state. Details of the technology and the first sensors results will be presented. The obtained ZnO nanorods are also applied in simple-architecture photovoltaic cells (efficiency over 12%) in conjunction with low-price Si substrates and high-sensitive photoresistors. Details informations about technology and applications will be presented.

Keywords: hydrothermal method, photoresistor, photovoltaic cells, ZnO nanorods

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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: Nay Myo Sandar

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With the growth of technologies and applications, a large amount of data has been producing at increasing rate from various resources such as social media networks, sensor devices, and other information serving devices. This large collection of massive, complex and exponential growth of dataset is called big data. The traditional database systems cannot store and process such data due to large and complexity. Consequently, cloud computing is a potential solution for data storage and processing since it can provide a pool of resources for servers and storage. However, moving large amount of data to and from is a challenging issue since it can encounter a high latency due to large data size. With respect to big data movement problem, this paper reviews the literature of previous works, discusses about research issues, finds out approaches for dealing with big data movement problem.

Keywords: Big Data, Cloud Computing, Big Data Movement, Network Techniques

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Authors: Fathi Kallel, Saida Khachira, Mohamed Ben Slima, Ahmed Ben Hamida

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Speckle noise is a main characteristic of cardiac ultrasound images, it corresponding to grainy appearance that degrades the image quality. For this reason, the ultrasound images are difficult to use automatically in clinical use, then treatments are required for this type of images. Then a filtering procedure of these images is necessary to eliminate the speckle noise and to improve the quality of ultrasound images which will be then segmented to extract the necessary forms that exist. In this paper, we present the importance of the pre-treatment step for segmentation. This work is applied to cardiac ultrasound images. In a first step, a comparative study of speckle filtering method will be presented and then we use a segmentation algorithm to locate and extract cardiac structures.

Keywords: medical image processing, ultrasound images, Speckle noise, image enhancement, speckle filtering, segmentation, snakes

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Authors: Michel Kulhandjian, Dimitris A. Pados

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The objective of this work is to develop a theoretical framework for reliable digital recording system identification from digital audio files alone, for forensic purposes. A digital recording system consists of a microphone and a digital sound processing card. We view the cascade as a system of unknown transfer function. We expect same manufacturer and model microphone-sound card combinations to have very similar/near identical transfer functions, bar any unique manufacturing defect. Input voice (or other) signals are modeled as non-stationary processes. The technical problem under consideration becomes blind deconvolution with non-stationary inputs as it manifests itself in the specific application of digital audio recording equipment classification.

Keywords: blind system identification, audio fingerprinting, blind deconvolution, blind dereverberation

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Authors: Avyarthana Dey, Naren P. Rao, Arpitha Jacob, Chaitra V. Hiremath, Shivarama Varambally, Ganesan Venkatasubramanian, Rose Dawn Bharath, Bangalore N. Gangadhar

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Objective: Impaired facial emotion recognition is widely reported in schizophrenia. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. However, its effect on facial emotion recognition deficits seen in schizophrenia is not well explored. In this study, we examined the effect of intranasal OXT on processing facial emotions and its neural correlates in patients with schizophrenia. Method: 12 male patients (age= 31.08±7.61 years, education= 14.50±2.20 years) participated in this single-blind, counterbalanced functional magnetic resonance imaging (fMRI) study. All participants underwent three fMRI scans; one at baseline, one each after single dose 24IU intranasal OXT and intranasal placebo. The order of administration of OXT and placebo were counterbalanced and subject was blind to the drug administered. Participants performed a facial emotion recognition task presented in a block design with six alternating blocks of faces and shapes. The faces depicted happy, angry or fearful emotions. The images were preprocessed and analyzed using SPM 12. First level contrasts comparing recognition of emotions and shapes were modelled at individual subject level. A group level analysis was performed using the contrasts generated at the first level to compare the effects of intranasal OXT and placebo. The results were thresholded at uncorrected p < 0.001 with a cluster size of 6 voxels. Neuropeptide oxytocin is known to modulate brain regions involved in facial emotion recognition, namely amygdala, in healthy volunteers. Results: Compared to placebo, intranasal OXT attenuated activity in inferior temporal, fusiform and parahippocampal gyri (BA 20), premotor cortex (BA 6), middle frontal gyrus (BA 10) and anterior cingulate gyrus (BA 24) and enhanced activity in the middle occipital gyrus (BA 18), inferior occipital gyrus (BA 19), and superior temporal gyrus (BA 22). There were no significant differences between the conditions on the accuracy scores of emotion recognition between baseline (77.3±18.38), oxytocin (82.63 ± 10.92) or Placebo (76.62 ± 22.67). Conclusion: Our results provide further evidence to the modulatory effect of oxytocin in patients with schizophrenia. Single dose oxytocin resulted in significant changes in activity of brain regions involved in emotion processing. Future studies need to examine the effectiveness of long-term treatment with OXT for emotion recognition deficits in patients with schizophrenia.

Keywords: recognition, functional connectivity, oxytocin, schizophrenia, social cognition

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Authors: Ahmed Mateen, Zhu Qingsheng, Ahmad Bilal

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In the current age of technology, information is the most precious asset of a company. Today, companies have a large amount of data. As the data become larger, access to data for some particular information is becoming slower day by day. Faster data processing to shape it in the form of information is the biggest issue. The major problems in distributed databases are the efficiency of data distribution and response time of data distribution. The security of data distribution is also a big issue. For these problems, we proposed a strategy that can maximize the efficiency of data distribution and also increase its response time. This technique gives better results for secure data distribution from multiple heterogeneous sources. The newly proposed technique facilitates the companies for secure data sharing efficiently and quickly.

Keywords: ER-schema, electronic record, P2P framework, API, query formulation

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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: Niharika Kaushal, Minni Singh

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Citrus fruits contain an abundance of phytochemicals that can promote health. A substantial amount of agrowaste is produced from the juice processing industries, primarily peels and seeds. This leftover agrowaste is a reservoir of nutraceuticals, particularly bioflavonoids which render it antioxidant and potentially anticancerous. It is, therefore, favorable to utilize this biomass and contribute towards sustainability in a manner that value-added products may be derived from them, nutraceuticals, in this study. However, the pre-systemic metabolism of flavonoids in the gastric phase limits the effectiveness of these bioflavonoids derived from mandarin biomass. In this study, ‘kinnow’ mandarin (Citrus nobilis X Citrus deliciosa) biomass was explored for its flavonoid profile. This work entails supercritical fluid extraction and identification of bioflavonoids from mandarin biomass. Furthermore, to overcome the limitations of these flavonoids in the gastrointestinal tract, a double-layered vehicular mechanism comprising the fabrication of nanoconjugates and edible hydrogels was adopted. Total flavonoids in the mandarin peel extract were estimated by the aluminum chloride complexation method and were found to be 47.3±1.06 mg/ml rutin equivalents as total flavonoids. Mass spectral analysis revealed the abundance of polymethoxyflavones (PMFs), nobiletin and tangeretin as the major flavonoids in the extract, followed by hesperetin and naringenin. Furthermore, the antioxidant potential was analyzed by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method, which showed an IC50 of 0.55μg/ml. Nanoconjugates were fabricated via the solvent evaporation method, which was further impregnated into hydrogels. Additionally, the release characteristics of nanoconjugate-laden hydrogels in a simulated gastrointestinal environment were studied. The PLGA-PMFs nanoconjugates exhibited a particle size between 200-250nm having a smooth and spherical shape as revealed by FE-SEM. The impregnated alginate hydrogels offered a dense network that ensured the holding of PLGA-PMF nanoconjugates, as confirmed by Cryo-SEM images. Rheological studies revealed the shear-thinning behavior of hydrogels and their high resistance to deformation. Gastrointestinal studies showed a negligible 4.0% release of flavonoids in the gastric phase, followed by a sustained release over the next hours in the intestinal environment. Therefore, based on the enormous potential of recovering nutraceuticals from agro-processing wastes, further augmented by nanotechnological interventions for enhancing the bioefficacy of these compounds, lays the foundation for exploring the path towards the development of value-added products, thereby contributing towards the sustainable use of agrowaste.

Keywords: agrowaste, gastrointestinal, hydrogel, nutraceuticals

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Authors: Natalia Efremova, Sergey Tarasenko

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We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

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Authors: Nishant Singh, Christian Huyck, Vaibhav Gandhi, Alexander Jones

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A robotic arm and hand controlled by simulated neurons is presented. The robot makes use of a biological neuron simulator using a point neural model. The neurons and synapses are organised to create a finite state automaton including neural inputs from sensors, and outputs to effectors. The robot performs a simple pick-and-place task. This work is a proof of concept study for a longer term approach. It is hoped that further work will lead to more effective and flexible robots. As another benefit, it is hoped that further work will also lead to a better understanding of human and other animal neural processing, particularly for physical motion. This is a multidisciplinary approach combining cognitive neuroscience, robotics, and psychology.

Keywords: cell assembly, force sensitive resistor, robot, spiking neuron

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Authors: Leorisyl D. Siarot

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It is conventional to see and hear Filipinos, in general, speak two or more languages. This phenomenon brings us to a closer look on how our minds process the input and produce an output with a specific chosen language. This study aimed to generate a theoretical model which explained the interaction of the first and the second languages in the human mind. After a careful analysis of the gathered data, a theoretical prototype called Language Activation Model was generated. For every string, there are three specialized banks: lexico-semantics, morphono-syntax, and pragmatics. These banks are interrelated to other banks of other language strings. As the bilingual learns more languages, a new string is replicated and is filled up with the information of the new language learned. The principles of the first and second languages' interaction are drawn; these are expressed in laws, namely: law of dominance, law of availability, law of usuality and law of preference. Furthermore, difficulties encountered in the learning of second languages were also determined.

Keywords: bilingualism, psycholinguistics, second language learning, languages

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Authors: Tokihiko Akita, Seiichi Mita

Abstract:

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: Nazli W. Hardy

Abstract:

A critical component in the Internet of Things (IoT) ecosystem is the need for secure and appropriate transmission, processing, and storage of the data. Our current forms of authentication, and identity and access management do not suffice because they are not designed to service cohesive, integrated, interconnected devices, and service applications. The seemingly endless opportunities of IoT are in fact circumscribed on multiple levels by concerns such as trust, privacy, security, loss of control, and related issues. This paper considers multi-factor authentication (MFA) mechanisms and cohesive identity relationship management (IRM) standards. It also surveys messaging protocols that are appropriate for the IoT ecosystem.

Keywords: identity relation management, multifactor authentication, protocols, survey of internet of things ecosystem

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Authors: Hamsini Pulugurtha, P. V. S. L. Jagadamba

Abstract:

Programmed Speech to Text and Text Summarization Using Graph-based Algorithms can be utilized in gatherings to get the short depiction of the gathering for future reference. This gives signature check utilizing Siamese neural organization to confirm the personality of the client and convert the client gave sound record which is in English into English text utilizing the discourse acknowledgment bundle given in python. At times just the outline of the gathering is required, the answer for this text rundown. Thus, the record is then summed up utilizing the regular language preparing approaches, for example, solo extractive text outline calculations

Keywords: Siamese neural network, English speech, English text, natural language processing, unsupervised extractive text summarization

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Authors: Merry Meryam Martgrita, Marselina Irasonia Tan

Abstract:

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

Procedia PDF Downloads 284

Authors: Logaiswari Indiran, Zainab Khalifah, Kamariah Ismail

Abstract:

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

Procedia PDF Downloads 275