Search results for: algebraic signal processing

Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

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Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: neural network, motion detection, signature detection, convolutional neural network

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Authors: Babar Khan, Wang Zhijie

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Machine Vision has been playing a significant role in Industrial Automation, to imitate the wide variety of human functions, providing improved safety, reduced labour cost, the elimination of human error and/or subjective judgments, and the creation of timely statistical product data. Despite the intensive research, there have not been any attempts to classify fabric prints based on printed texture and colour, most of the researches so far encompasses only black and white or grey scale images. We proposed a biologically inspired processing architecture to classify fabrics w.r.t. the fabric print texture and colour. We created a texture descriptor based on the HMAX model for machine vision, and incorporated colour descriptor based on opponent colour channels simulating the single opponent and double opponent neuronal function of the brain. We found that our algorithm not only outperformed the original HMAX algorithm on classification of fabric print texture and colour, but we also achieved a recognition accuracy of 85-100% on different colour and different texture fabric.

Keywords: automatic classification, texture descriptor, colour descriptor, opponent colour channel

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Authors: Bernard Bladergroen, David Vlotman, Bradley Cerff

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The agricultural sector is one which requires and consumes large amounts of water globally. Commercial wine production, in particular, uses extensive volumes of fresh water and generates significant volumes of wastewater through various processes. The wastewater produced by wineries typically exhibits elevated levels of chemical oxygen demand (COD), total suspended solids (TSS), total dissolved solids (TDS), acidic pH and varying salinity and nutrient contents. This study investigates the performance of a shear-enhanced flotation separation (SEFS) pilot plant as a primary treatment stage during winery wastewater processing by modifying a conventional Dissolved Air Flotation (DAF) system. The SEFS pilot plant achieved a 99% reduction in both turbidity and TSS in comparison to the 97% achieved with the conventional DAF system. The COD was reduced by 66% and 51% for the SEFS and DAF systems, respectively. SEFS shows the advantages of hydrodynamic shear to enhance the coagulation and subsequent flocculation processes with a significant reduction of coagulant and flocculant (36% and 31%, respectively).

Keywords: shear enhanced flotation, suspended solids, primary wastewater treatment, zeta potential

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Authors: Ashraf Ward

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Effect of calving interval on 305 day milk yield for first three lactations was studied in order to increase efficiency of selection schemes and to more efficiently manage Holstein cows that have been raised on small farms in Libya. Results obtained by processing data of 1476 cows, managed in 935 small scale farms, pointed out that current calving interval significantly affects on milk production for first three lactations (p<0.05). Preceding calving interval affected 305 day milk yield (p<0.05) in second lactation only. Linear regression model accounted for 20-25 % of the total variance of 305 day milk yield. Extension of calving interval over 420, 430, 450 days for first, second and third lactations respectively, did not increase milk production when converted to 305 day lactation. Stochastic relations between calving interval and calving age and month are moderated. Values of Pierson’s correlation coefficients ranged 0.38 to 0.69. Adjustment of milk production in order to reduce effect of calving interval on total phenotypic variance of milk yield is valid for first lactation only. Adjustment of 305 day milk yield for second and third lactations in order to reduce effects of factors “calving age and month” brings about, at the same time, elimination of calving interval effect.

Keywords: milk yield, Holstien, non genetic, calving

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Authors: P. Senthil Kumari

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Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

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Authors: Julien Baillet

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In light of 30 years of scientific research, InCorporer Method was created in 2019 as a new approach to heal traumatic, developmental, and dissociative injuries. Following natural nervous system functions, InCorporer aims to heal, develop, and update the different defensive mammalian subsystems: fight, flight, freeze, feign death, cry for help, & energy regulator. The dimensions taken into account are: (i) Heal the traumatic injuries who are still bleeding, (ii) Develop the systems that never received the security, attention, and affection they needed. (iii) Update the parts that stayed stuck in the past, ignoring for too long that they are out of danger now. Through the Present Part and its caregiving skills, InCorporer method enables a balanced, soothed, and collaborative personality system. To be as integrative as possible, InCorporer method has been designed according to several fields of research, such as structural dissociation theory, attachment theory, and information processing theory. In this paper, the author presents how the internal caregiver is developed and trained to heal all the different parts/subsystems of our clients through mindful attention and reflex movement integration.

Keywords: PTSD, attachment, dissociation, part work

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Authors: Magarò Floriana, Zinno Raffaele

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Since 2009, with the coming into force of the January 14, 2008 Ministerial Decree "New technical standards for construction", and the explanatory ministerial circular N°.617 of February 2, 2009, the question of seismic hazard and the design of seismic-resistant structures in Italy has acquired increasing importance. One of the most discussed aspects in recent Italian and international scientific literature concerns the dynamic interaction between land and structure, and the effects which dynamic coupling may have on individual buildings. In effect, from systems dynamics, it is well known that resonance can have catastrophic effects on a stimulated system, leading to a response that is not compatible with the previsions in the design phase. The method used in this study to estimate the frequency of oscillation of the structure is as follows: the analysis of HVSR (Horizontal to Vertical Spectral Ratio) relations. This allows for evaluation of very simple oscillation frequencies for land and structures. The tool used for data acquisition is an experimental digital tromograph. This is an engineered development of the experimental Languamply RE 4500 tromograph, equipped with an engineered amplification circuit and improved electronically using extremely small electronic components (size of each individual amplifier 16 x 26 mm). This tromograph is a modular system, completely "free" and "open", designed to interface Windows, Linux, OSX and Android with the outside world. It an amplifier designed to carry out microtremor measurements, yet which will also be useful for seismological and seismic measurements in general. The development of single amplifiers of small dimension allows for a very clean signal since being able to position it a few centimetres from the geophone eliminates cable “antenna” phenomena, which is a necessary characteristic in seeking to have signals which are clean at the very low voltages to be measured.

Keywords: microtremor, HVSR, tromograph, structural engineering

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Authors: Reyhan Özdoğan, Özgür Ceylan, Mehmet Arif Kaya, Mithat Çelebi

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Food packaging is important for the food industry. Bioplastics have been used as food packaging materials. According to the European Bioplastics organization, bioplastics can be defined as plastics based on renewable resources (bio-based) or as plastics which are biodegradable and/or compostable. Poly(lactic acid) (PLA) has an industrially importance of bioplastic polymers. PLA is a family of biodegradable thermoplastic polyester made from renewable resources. It is produced by conversion of corn, or other carbohydrate sources, into dextrose, followed by fermentation into lactic acid through direct polycondensation of lactic acid monomers or through ring-opening polymerization of lactide. The processing possibilities of this transparent material are very wide, ranging from injection molding and extrusion over cast film extrusion to blow molding and thermoforming. In this study, PLA films were prepared by solution casting method. PLAs which are different molecular weights were plasticized with glycerol and the morphology of films was monitored by optical microscopy. Properties of mechanical and film of PLA were researched with the mechanical testing machine.

Keywords: biodegradable, bioplastics, morphology, solution casting, poly(lactic acid)

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Authors: Ramkumar Gunasekaran, John Cater, Vinod Suresh, Haribalan Kumar

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The main objective of this project is to develop a statistical shape model using principal component analysis that could be used for analyzing the shape of the human airway. The ultimate goal of this project is to identify geometric risk factors for diagnosis and management of Obstructive Sleep Apnoea (OSA). Anonymous CBCT scans of 25 individuals were obtained from the Otago Radiology Group. The airways were segmented between the hard-palate and the aryepiglottic fold using snake active contour segmentation. The point data cloud of the segmented images was then fitted with a bi-cubic mesh, and pseudo landmarks were placed to perform PCA on the segmented airway to analyze the shape of the airway and to find the relationship between the shape and OSA risk factors. From the PCA results, the first four modes of variation were found to be significant. Mode 1 was interpreted to be the overall length of the airway, Mode 2 was related to the anterior-posterior width of the retroglossal region, Mode 3 was related to the lateral dimension of the oropharyngeal region and Mode 4 was related to the anterior-posterior width of the oropharyngeal region. All these regions are subjected to the risk factors of OSA.

Keywords: medical imaging, image processing, FEM/BEM, statistical modelling

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Authors: Chiara De Amicis, Sonia Falconieri, Mesut Tastan

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In this study, we analyze the language employed by Chief Executive Officers (CEOs) and Chief Financial Officers (CFOs) during earnings conference calls from a gender perspective. We find evidences that conference calls held by female CEOs and/or CFOs exhibit a higher level of optimism compared to conference calls held by male CEOs and/or CFOs. Moreover, female managers tend to present and discuss firm performances with less vagueness as compared to their male colleagues. We then observe the market reaction around each earnings conference call: while manager optimism is perceived as a good signal by investors, manager vagueness significantly dampens the market reaction around the call. Whether the gender of the CEO and/or the CFO delivering the conference call affects investors’ perceptions about the firm performance is still an open question. Some evidences show that the language employed by female managers conveys more valuable information for market participants as compared to the language employed by their male counterparts. This study contributes to a growing literature in finance and accounting that uses textual analysis to assess the informativeness of corporate disclosure. To our knowledge, this is the first paper that aims at answering the question whether the gender of firm’s top managers does matter when it comes to assess the informativeness of corporate spoken communication. We believe that our results will be of relevance for future research in the field. Moreover, our evidence may be used in support of the debate if a larger participation by women in the management of companies should be encouraged or not.

Keywords: conference calls, even study, gender, market reaction, textual analysis

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Authors: Mohamed R. Mhereeg

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The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). Microsoft's .NET windows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Keywords: MACS, implementation, multi-agent, SOA, autonomous, WCF

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Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

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This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

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Authors: Teh Kean Kheng, Low Soon Yee, Burra Venkata Durga Kumar

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In 2022, as the future world becomes increasingly computer-related, more individuals are attempting to study coding for themselves or in school. This is because they have discovered the value of learning code and the benefits it will provide them. But learning coding is difficult for most people. Even senior programmers that have experience for a decade year still need help from the online source while coding. The reason causing this is that coding is not like talking to other people; it has the specific syntax to make the computer understand what we want it to do, so coding will be hard for normal people if they don’t have contact in this field before. Coding is hard. If a user wants to learn bash code with bash prompt, it will be harder because if we look at the bash prompt, we will find that it is just an empty box and waiting for a user to tell the computer what we want to do, if we don’t refer to the internet, we will not know what we can do with the prompt. From here, we can conclude that the bash prompt is not user-friendly for new users who are learning bash code. Our goal in writing this paper is to give an idea to implement a user-friendly Bash prompt in Ubuntu OS using Artificial Intelligent (AI) to lower the threshold of learning in Bash code, to make the user use their own words and concept to write and learn Bash code.

Keywords: user-friendly, bash code, artificial intelligence, threshold, semantic similarity, lexical similarity

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Authors: Anastasia Rita Widiarti, Agus Harjoko, Marsono, Sri Hartati

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This paper presents the results of a study to test whether the Javanese character manuscript image preprocessing model that have been more widely applied, can also be applied to segment of the Batak characters manuscripts. The treatment process begins by converting the input image into a binary image. After the binary image is cleaned of noise, then the segmentation lines using projection profile is conducted. If unclear histogram projection is found, then the smoothing process before production indexes line segments is conducted. For each line image which has been produced, then the segmentation scripts in the line is applied, with regard of the connectivity between pixels which making up the letters that there is no characters are truncated. From the results of manuscript preprocessing system prototype testing, it is obtained the information about the system truth percentage value on pieces of Pustaka Batak Podani Ma AjiMamisinon manuscript ranged from 65% to 87.68% with a confidence level of 95%. The value indicates the truth percentage shown the initial processing model in Javanese characters manuscript image can be applied also to the image of the Batak characters manuscript.

Keywords: connected component, preprocessing, manuscript image, projection profiles

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Authors: A. Benmoussa, M. Bouanini, M. Rebhi

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The mixing and agitation of fluid in stirred tank is one of the most important unit operations for many industries such as chemical, biotechnological, pharmaceutical, petrochemical, cosmetic, and food processing. Therefore, determining the level of mixing and overall behaviour and performance of the mixing tanks are crucial from the product quality and process economics point of views. The most fundamental needs for the analysis of these processes from both a theoretical and industrial perspective is the knowledge of the hydrodynamic behaviour and the flow structure in such tanks. Depending on the purpose of the operation carried out in mixer, the best choice for geometry of the tank and agitator type can vary widely. Initially, a local and global study namely the velocity and power number on a typical agitation system agitated by a mobile-type two-blade straight (d/D=0.5) allowed us to test the reliability of the CFD, the result were compared with those of experimental literature, a very good concordance was observed. The stream function, the velocity profile, the velocity fields and power number are analyzed. It was shown that the hydrodynamics is modified by the curvature of the mobile which plays a key role.

Keywords: agitated tanks, curved blade agitator, laminar flow, CFD modelling

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Authors: JiYoung Park, SueGoo Rhee, HyunAe Woo

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In liver regeneration, quiescent hepatocytes need to be primed to fully respond to growth factors such as hepatocyte growth factor. To understand the priming process, it is necessary to analyze patterns of gene expression that occur during liver regeneration after partial hepatectomy (PHx). Recently, tyrosine phosphorylation of signal transducer and activator of transcription 3 (pYSTAT3) has been shown to play an important role in initiating liver regeneration. In order to evaluate the role of pYSTAT3 on liver regeneration after PHx, we used an intrabody which can selectively inhibit pYSTAT3. In our previous studies, an intrabody had been shown that it bound specifically to the pYSTAT3. Adenovirus-mediated expression of the intrabody in HepG2 cells, as well as mouse liver, blocked both accumulation of pYSTAT3 in the nucleus and downstream target of pYSTAT3. In this study, PHx was performed on intrabody-expressing mice and the expression levels of liver regeneration-related genes were analyzed. We also measured liver/body weight ratios and the related cellular signaling pathways were analyzed. Acute phase response genes were reduced in an intrabody-expressing mice during liver regeneration than in control virus-injected mice. However, the time course of liver mass restoration in intrabody-expressing mice was similar to that observed in control virus-injected mice. We also observed that the expression levels of anti-apoptotic genes, such as Bcl2 and Bcl-xL were decreased in intrabody-expressing mice whereas the expression of cell cycle-related genes such as cyclin D1, and c-myc was increased. Liver regeneration after PHx was partially impaired by the selective inhibition of pYSTAT3 with a phosphorylation site-specific intrabody and these results indicated that pYSTAT3 might have limited role in liver mass recovery.

Keywords: STAT3, pYSTAT3, liver regeneration, intrabody

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Authors: S. Alansary, M. Nagi

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This paper presents an approach of conducting semantic annotation of Arabic corpus using the Universal Networking Language (UNL) framework. UNL is intended to be a promising strategy for providing a large collection of semantically annotated texts with formal, deep semantics rather than shallow. The result would constitute a semantic resource (semantic graphs) that is editable and that integrates various phenomena, including predicate-argument structure, scope, tense, thematic roles and rhetorical relations, into a single semantic formalism for knowledge representation. The paper will also present the Interactive Analysis​ tool for automatic semantic annotation (IAN). In addition, the cornerstone of the proposed methodology which are the disambiguation and transformation rules, will be presented. Semantic annotation using UNL has been applied to a corpus of 20,000 Arabic sentences representing the most frequent structures in the Arabic Wikipedia. The representation, at different linguistic levels was illustrated starting from the morphological level passing through the syntactic level till the semantic representation is reached. The output has been evaluated using the F-measure. It is 90% accurate. This demonstrates how powerful the formal environment is, as it enables intelligent text processing and search.

Keywords: semantic analysis, semantic annotation, Arabic, universal networking language

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Authors: Yu Zhang, Ye Tian, Fang Ye Yixuan Kang

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The capacity of conventional cellular networks has reached its upper bound and it can be well handled by introducing femtocells with low-cost and easy-to-deploy. Spectrum interference issue becomes more critical in peace with the value-added multimedia services growing up increasingly in two-tier cellular networks. Spectrum allocation is one of effective methods in interference mitigation technology. This paper proposes a game-theory-based on OFDMA downlink spectrum allocation aiming at reducing co-channel interference in two-tier femtocell networks. The framework is formulated as a non-cooperative game, wherein the femto base stations are players and frequency channels available are strategies. The scheme takes full account of competitive behavior and fairness among stations. In addition, the utility function reflects the interference from the standpoint of channels essentially. This work focuses on co-channel interference and puts forward a negative logarithm interference function on distance weight ratio aiming at suppressing co-channel interference in the same layer network. This scenario is more suitable for actual network deployment and the system possesses high robustness. According to the proposed mechanism, interference exists only when players employ the same channel for data communication. This paper focuses on implementing spectrum allocation in a distributed fashion. Numerical results show that signal to interference and noise ratio can be obviously improved through the spectrum allocation scheme and the users quality of service in downlink can be satisfied. Besides, the average spectrum efficiency in cellular network can be significantly promoted as simulations results shown.

Keywords: femtocell networks, game theory, interference mitigation, spectrum allocation

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Authors: Ali Al-Dahoud, Mohamed Fezari, Thamer Al-Rawashdeh, Ismail Jannoud

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Monitoring and detecting faults on a set of Solar panels, using a wireless sensor network (WNS) is our contribution in this paper, This work is part of the project we are working on at Al-Zaytoonah University. The research problem has been exposed by engineers and technicians or operators dealing with PV panels maintenance, in order to monitor and detect faults within solar panels which affect considerably the energy produced by the solar panels. The proposed solution is based on installing WSN nodes with appropriate sensors for more often occurred faults on the 45 solar panels installed on the roof of IT faculty. A simulation has been done on nodes distribution and a study for the design of a node with appropriate sensors taking into account the priorities of the processing faults. Finally, a graphic user interface is designed and adapted to telemonitoring panels using WSN. The primary tests of hardware implementation gave interesting results, the sensors calibration and interference transmission problem have been solved. A friendly GUI using high level language Visial Basic was developed to carry out the monitoring process and to save data on Exel File.

Keywords: Arduino Mega microcnotroller, solar panels, fault-detection, simulation, node design

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Authors: Nneka Nkechi Uchegbu, Temitope Omolayo Fasuan

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This study investigated how to reduce bio-compounds and amino acids in V. amygdalina leaf during processing as a functional food ingredient. Fresh V. amygdalina leaf was processed using thermal oil-aqueous mixtures (soybean oil: aqueous and palm oil: aqueous) at 1:40 and 130 (v/v), respectively. Results indicated that the hot soybean oil-aqueous mixture was the most effective in preserving the bio-compounds and amino acids with retention potentials of 80.95% of the bio-compounds at the rate of 90-100%. Hot palm oil-aqueous mixture retained 61.90% of the bio-compounds at the rate of 90-100% and hot aqueous retained 9.52% of the bio-compounds at the same rate. During the debittering process, seven new bio-compounds were formed in the leaves treated with hot soybean oil-aqueous mixture, six in palm oil-aqueous mixture, and only four in hot aqueous leaves. The bio-compounds in the treated leaves have potential functions as antitumor, antioxidants, antihistaminic, anti-ovarian cancer, anti-inflammatory, antiarthritic, hepatoprotective, antihistaminic, haemolytic 5-α reductase inhibitor, nt, immune-stimulant, diuretic, antiandrogenic, and anaemiagenic. Alkaloids and polyphenols were retained at the rate of 81.34-98.50% using oil: aqueous mixture while aqueous recorded the rate of 33.47-41.46%. Most of the essential amino acids were retained at a rate above 90% through the aid of oil. The process is scalable and could be employed for domestic and industrial applications.

Keywords: V. amygdalina leaf, bio-compounds, oil-aqueous mixture, amino acids

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Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

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Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: pollen recognition, logistic model tree, expectation-maximization, local binary pattern

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Authors: Miriam Sebastian

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This research focused on the effects of bilingual education as medium of instruction to the academic performance of selected intermediate students of Miriam’s Academy of Valenzuela Inc. . An experimental design was used, with language of instruction as the independent variable and the different literacy skills as dependent variables. The sample consisted of experimental students comprises of 30 students were exposed to bilingual education (Filipino and English) . They were given pretests and were divided into three groups: Monolingual Filipino, Monolingual English, and Bilingual. They were taught different literacy skills for eight weeks and were then administered the posttests. Data was analyzed and evaluated in the light of the central processing and script-dependent hypotheses. Based on the data, it can be inferred that monolingual instruction in either Filipino or English had a stronger effect on the students’ literacy skills compared to bilingual instruction. Moreover, mother tongue-based instruction, as compared to second-language instruction, had stronger effect on the preschoolers’ literacy skills. Such results have implications not only for mother tongue-based (MTB) but also for English as a second language (ESL) instruction in the country

Keywords: bilingualism, effects, monolingual, function, multilingual, mother tongue

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Authors: Jinyoung Park, Eun Joo Song

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Introduction: Deubiquitinating enzymes (DUBs) are proteases that cleave ubiquitin or ubiquitin-like modifications on substrates. Deubiquitination could regulate cellular physiology, such as signal transduction, DNA damage and repair, and cell cycle progression. Although more than 100 DUBs are encoded in the human and the importance of DUBs has been realized, the functions of most DUBs are unknown. This study aims to identify the molecular mechanism by which deubiquitinating enzyme USP35 regulates cell cycle progression for the first time. Methods: USP35 RNAi was mainly used to identify the function of USP35 in cell cycle progression. To find substrates of USP35, we analyzed protein-protein interaction using LC-MS. Several biological methods, such as ubiquitination assay, cell synchronization, immunofluorescence, and immunoprecipitation assay were used to investigate the exact mechanism by which USP35 affects successful completion of mitosis. Results: USP35 knockdown caused not only reduction of mitotic cell number but also induction of mitotic cells with abnormal spindle formation. Actually, cell proliferation was decreased by USP35 knockdown. Interestingly, we found that loss of USP35 decreased the stability and expression of Aurora B, a member of chromosomal passenger complex (CPC), and the phosphorylation of its substrate. Indeed, USP35 interacted with Aurora B and deubiquitinated it. In addition, USP35 knockdown induced abnormal localization of Aurora B in mitotic cells. Finally, CDH1-mediated ubiquitination of Aurora B level was rescued by USP35 overexpression, but not inactive form of USP35, USP35 C450A. Discussion: Our findings suggest that USP35 regulates Aurora B-mediated mitotic spindle assembly and G2-M transition by blocking CDH1-induced degradation of Aurora B.

Keywords: USP35, HSP90, Aurora B, cell cycle progression

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Authors: Pravat Ranjan Pati, Alok Satapathy

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Linz-Donawitz (LD) slag a major solid waste generated in huge quantities during steel making. It comes from slag formers such as burned lime/dolomite and from oxidizing of silica, iron etc. while refining the iron into steel in the LD furnace. Although a number of ways for its utilization have been suggested, its potential as a filler material in polymeric matrices has not yet been explored. The present work reports the possible use of this waste in glass fiber reinforced epoxy composites as a filler material. Hybrid composites consisting of bi-directional e-glass-fiber reinforced epoxy filled with different LD slag content (0, 7.5, 15, 22.5 wt%) are prepared by simple hand lay-up technique. The composites are characterized in regard to their density, porosity, micro-hardness and strength properties. X-ray diffractography is carried out in order to ascertain the various phases present in LDS. This work shows that LD slag, in spite of being a waste, possesses fairly good filler characteristics as it modifies the strength properties and improves the composite micro-hardness of the polymeric resin.

Keywords: characterization, glass-epoxy composites, LD slag, waste utilization

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Authors: Asmau Mukhtar Ahmed, Olga Duran

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Hydrocarbon (HC) spills constitute a significant problem that causes great concern to the environment. With the latest technology (hyperspectral images) and state of the earth techniques (image processing tools), hydrocarbon spills can easily be detected at an early stage to mitigate the effects caused by such menace. In this study; a controlled laboratory experiment was used, and clay soil was mixed and homogenized with different hydrocarbon types (diesel, bio-diesel, and petrol). The different mixtures were scanned with HYSPEX hyperspectral camera under constant illumination to generate the hypersectral datasets used for this experiment. So far, the Short Wave Infrared Region (SWIR) has been exploited in detecting HC spills with excellent accuracy. However, the Near-Infrared Region (NIR) is somewhat unexplored with regards to HC contamination and how it affects the spectrum of soils. In this study, Deep Neural Network (DNN) was applied to the controlled datasets to detect and quantify the amount of HC spills in soils in the Near-Infrared Region. The initial results are extremely encouraging because it indicates that the DNN was able to identify features of HC in the Near-Infrared Region with a good level of accuracy.

Keywords: hydrocarbon, Deep Neural Network, short wave infrared region, near-infrared region, hyperspectral image

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Authors: Giuseppe Spampinato, Salvatore Curti, Ivana Guarneri, Arcangelo Bruna

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This document describes an advanced system and methodology for Cross Traffic Alert (CTA), able to detect vehicles that move into the vehicle driving path from the left or right side. The camera is supposed to be not only on a vehicle still, e.g. at a traffic light or at an intersection, but also moving slowly, e.g. in a car park. In all of the aforementioned conditions, a driver’s short loss of concentration or distraction can easily lead to a serious accident. A valid support to avoid these kinds of car crashes is represented by the proposed system. It is an extension of our previous work, related to a clustering system, which only works on fixed cameras. Just a vanish point calculation and simple optical flow filtering, to eliminate motion vectors due to the car relative movement, is performed to let the system achieve high performances with different scenarios, cameras and resolutions. The proposed system just uses as input the optical flow, which is hardware implemented in the proposed platform and since the elaboration of the whole system is really speed and power consumption, it is inserted directly in the camera framework, allowing to execute all the processing in real-time.

Keywords: clustering, cross traffic alert, optical flow, real time, vanishing point

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Authors: Ruchi Yadav, Shivani Pandey, Prachi Srivastava

Abstract:

Microarrays provide a rich source of data on the molecular working of cells. Each microarray reports on the abundance of tens of thousands of mRNAs. Virtually every human disease is being studied using microarrays with the hope of finding the molecular mechanisms of disease. Bioinformatics analysis plays an important part of processing the information embedded in large-scale expression profiling studies and for laying the foundation for biological interpretation. A basic, yet challenging task in the analysis of microarray gene expression data is the identification of changes in gene expression that are associated with particular biological conditions. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. One of the most popular platforms for microarray analysis is Bioconductor, an open source and open development software project based on the R programming language. This paper describes specific procedures for conducting quality assessment, visualization and preprocessing of Affymetrix Gene Chip and also details the different bioconductor packages used to analyze affymetrix microarray data and describe the analysis and outcome of each plots.

Keywords: microarray analysis, R language, affymetrix visualization, bioconductor

Procedia PDF Downloads 480

Authors: Victor Pesco Kassa

Abstract:

This research deals with the assessment of the contribution of GIS Technology in NRW. This research was conducted at Dar, Kawe Mzimuni Street. The data collection was obtained from existing source which is DAWASA HQ. The interpretation of the data was processed by using ArcGIS software. The data collected from the existing source reveals a good coverage of DAWASA’s water network at Mzimuni Street. Most of residents are connected to the DAWASA’s customer service. Also the collected data revealed that by using GIS DAWASA’s customer Geodatabase has been improved. Through GIS we can prepare customer location map purposely for site surveying also this map will be able to show different type of customer that are connected to DAWASA’s water service. This is a perfect contribution of the GIS Technology to address and manage the problem of NRW in DAWASA. Finally, the study recommends that the same study should be conducted in other DAWASA’s zones such as Temeke, Boko and Bagamoyo not only at Kawe Mzimuni Street. Through this study it is observed that ArcGIS software can offer powerful tools for managing and processing information geographically and in water and sanitation authorities such as DAWASA.

Keywords: DAWASA, NRW, Esri, EURA, ArcGIS

Procedia PDF Downloads 84

Authors: Marwan Jarrah

Abstract:

This research paper provides two pieces of phonological and syntactic evidence from Arabic for biolinguistics perspective of language processing. The first piece of evidence concerns the instances where a singular noun is converted to a plural noun in Arabic. Based on the findings of several research papers, this study shows that a singular word does not lose any of its moras when it is pluralized either regularly or irregularly. This mora conservation principle complies with the general physical law of the conservation of mass which states that mass is neither created nor destroyed but changed from one form into another. The second piece of evidence concerns the observation that when the object in some Arabic dialects including Jordanian Arabic and Najdi Arabic is a topic and positioned in situ (i.e. after the verb), the verb agrees with it, something that generates an agreeing inflection marker of the verb that agrees in Number, Person, and Gender with the in-situ topicalized object. This interaction between the verb and the object in such cases is invoked because of the extra feature the object bears, i.e. TOPIC feature. We suggest that such an interaction complies with the general natural law that elements become active when they, e.g., get an additional electron, when the mass number is not equal to the atomic number.

Keywords: biolinguistics, Arabic, physics, interaction

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Authors: Yousif Mohamed Y. Abdallah, Eltayeb Wagallah

Abstract:

Image enhancement allows the observer to see details in images that may not be immediately observable in the original image. Image enhancement is the transformation or mapping of one image to another. The enhancement of certain features in images is accompanied by undesirable effects. To achieve maximum image quality after denoising, a new, low order, local adaptive Gaussian scale mixture model and median filter were presented, which accomplishes nonlinearities from scattering a new nonlinear approach for contrast enhancement of bones in bone scan images using both gamma correction and negative transform methods. The usual assumption of a distribution of gamma and Poisson statistics only lead to overestimation of the noise variance in regions of low intensity but to underestimation in regions of high intensity and therefore to non-optional results. The contrast enhancement results were obtained and evaluated using MatLab program in nuclear medicine images of the bones. The optimal number of bins, in particular the number of gray-levels, is chosen automatically using entropy and average distance between the histogram of the original gray-level distribution and the contrast enhancement function’s curve.

Keywords: bone scan, nuclear medicine, Matlab, image processing technique

Procedia PDF Downloads 512