Search results for: Color Structure-Texture Image Decomposition

Authors: Ghazi Abdul Rehman Qasmi

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Islam is the preacher and torch-bearer of unity and solidarity. All the followers of Islam are advised to be united. Islam strongly condemns those elements which disunite the unity of Muslim Ummah. Like pearls in a rosary, Islam has united the Muslims from all over the world in the wreath of unity and forbade the Muslims to avoid separation and to be disintegrated. The aspect of unity is prominent in all divine injunctions and about worship. By offering five times obligatory congregational prayers, passion of mutual love and affection is increased and on the auspicious days like Friday, Eid-ul-fiter and Eid-ul-azha, majority of the Muslims come together at central places to offer these congregational prayers. Thus unity and harmony among the Muslims can be seen. Similarly the Muslim pilgrims from all over the world eliminate all kind of worldly discrimination to perform many rituals of pilgrimage while wearing white color cloth as a dress. Pilgrimage is a demonstration of Islamic strength. When the Muslims from all over the world perform the same activities together and they offer their prayers under the leadership of one leader (IMAM). Muslims come together on the occasion of pilgrimage to perform Tawaf (seven circuits,first three circuits at a hurried pace(Rammal) and followed by four times, more closely, at a leisurely pace, round the Holy Kaabah to perform circumambulation known as Tawaf in religious terminology,Saee(running or walking briskly seven times between two small hills Safa&Marwa), Ramy-al-jamarat (throwing pebbles at the stone pillars, symbolizing the devil). In this way dignity and sublimity of Islam is increased and unity and integrity of Muslim Ummah is promoted also. By studying the life history of Hazrat Muhammad (P.B.U.H) we come to know that our Holy Prophet (P.B.U.H) has put emphasis on unity and integrity. We have to follow the Islamic teachings to create awareness among the members of Muslim Ummah. In the light of the Holy Quran and Sunnah, we have to utilize all the sources and potential for this noble cause.

Keywords: unity, Ummah, sources, Islamic teaching

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Authors: Kelemewerk Destalem, Joongjae Cho, Jaeseong Lee, Ju H. Park, Joonhyuk Yoo

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Background subtraction and temporal difference are often used for moving object detection in video. Both approaches are computationally simple and easy to be deployed in real-time image processing. However, while the background subtraction is highly sensitive to dynamic background and illumination changes, the temporal difference approach is poor at extracting relevant pixels of the moving object and at detecting the stopped or slowly moving objects in the scene. In this paper, we propose a moving object detection scheme based on adaptive background subtraction and temporal difference exploiting dynamic background updates. The proposed technique consists of a histogram equalization, a linear combination of background and temporal difference, followed by the novel frame-based and pixel-based background updating techniques. Finally, morphological operations are applied to the output images. Experimental results show that the proposed algorithm can solve the drawbacks of both background subtraction and temporal difference methods and can provide better performance than that of each method.

Keywords: background subtraction, background updating, real time, light weight algorithm, temporal difference

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Authors: Paulo Cesar Pereira Junior, Alexandre Monteiro, Rafael da Luz Ribeiro, Antonio Carlos Sobieranski, Aldo von Wangenheim

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In this paper, we present a comparison between convolutional neural networks and classical computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models.

Keywords: convolutional neural networks, deep learning, digital image processing, precision agriculture, semantic segmentation, unmanned aerial vehicles

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Authors: Maximo Cozzetti

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The aim is to evaluate the capability of the 'Siberian Husky' (FCI-Standard Nº 270) breed of the common dog (Canis lupus familiaris) to detect terminally-ill human patients undergoing palliative care. A total of 49 such patients that fulfill the 'National Scientific and Technical Research Council–Ethical Principles for the Behavior of the Scientific and Technical Investigator' policy, (mainly affected with Stage IV Hodgkin lymphoma or Stage IV Carcinoma, though various other terminal diseases were present) and 49 controls were enrolled. A total of 13 specimens of Siberian Huskies (Canis lupus familiaris FCI – Standard Nº 270) were selected. After a conditioning training regime in which the canines were rewarded when identifying terminally ill patients and excluding the control subjects, a double-blind experiment was conducted in which the canines were presented with a previously unknown patient through an olfactory-proof plexiglass window for 2-minute intervals. The test subjects correctly identified 89.80% of the humans as either ‘ill’ or ‘healthy’. It is important to note that both groups of humans were selected considering and preventing confounding and self-identifying factors such as age, ethnicity, clothing, posture, skin color, alopecia (chemotherapy-induced or otherwise), etc. The olfactory-proofing of the test area rules out the use of the sense of smell to detect distinctive drugs or bodily odors that may be associated with terminal diseases. Thus, the Siberian Husky breed of the common dog shows the visual capability to detect and identify terminally ill patients undergoing palliative care regardless of age, posture, and quantity of hair. Though the capability of the breed of dog to detect terminally-ill patients was observed thoroughly during the course of the experiments, the exact process by which the canines identify the test subjects remains unknown and further research is encouraged.

Keywords: Canis lupus familiaris, Siberian Husky, visual identification of terminall illness, FCI-Standard Nº270

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Authors: Anuja Singh, Avik K. Pati, Ashok K. Mishra

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Organic fluorophores with π-conjugated scaffolds are important because of their interesting optoelectronic properties. In recent years, our lab has been engaged in understanding the photophysics of small diacetylene bridged fluorophores and found the diynes as a promising class of π-conjugated fluorophores. Building on this understanding, recently we have focused on the photophysics of a less explored class of cross-conjugated Y-shaped enediynes (one double and two triple bonds). Here we present the photophysical properties of such enediynes which show interesting photophysical properties that include dual emissions from locally excited (LE) and intramolecular charge transfer (ICT) states and ring size dependent aggregate fluorescence in non-aqueous media. The dyes also show prominent aggregate fluorescence in mixed-aqueous solvents and solid powder form. We further show that the solid state fluorescence can be reversibly switched multiple of cycles by external stimuli, highlighting their potential applications in solid states. The enediynes with push-pull electronic substituents/moieties exhibit high contrast fluorescence color switching upon continuous photon illumination. The intriguing photophysical outcomes of the enediynyl fluorophores are judiciously exploited to generate single-component white light emission in binary solvent mixtures and sense polar aprotic vapor in polymer film matrices. The photophysical behavior of the dyes is further successfully utilized to monitor the microenvironment changes of biologically relevant anisotropic media such as bile salts. In summary, the newly introduced cross-conjugated enediynes enrich the toolbox of organic fluorophores and vouch to display versatile applications.

Keywords: aggregation in solution and solid state, enediynes, physical photochemistry and photophysics, vapor sensing and white light emission

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Authors: Bikshalu Kalagadda, Srikanth Rangu

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The important object of images segmentation is to extract objects with respect to some input features. One of the important methods for image segmentation is Level set method. Generally medical images and synthetic images with low contrast of pixel profile, for such images difficult to locate interested features in images. In conventional level set function, develops irregularity during its process of evaluation of contour of objects, this destroy the stability of evolution process. For this problem a remedy is proposed, a new hybrid algorithm is Clustering Level Set Evolution. Kernel fuzzy particles swarm optimization clustering with the Distance Regularized Level Set (DRLS) and Selective Binary, and Gaussian Filtering Regularized Level Set (SBGFRLS) methods are used. The ability of identifying different regions becomes easy with improved speed. Efficiency of the modified method can be evaluated by comparing with the previous method for similar specifications. Comparison can be carried out by considering medical and synthetic images.

Keywords: segmentation, clustering, level set function, re-initialization, Kernel fuzzy, swarm optimization

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Authors: Najeh Lakhoua

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Introduction: Scientific developments and techniques for the systemic approach generate several names to the systemic approach: systems analysis, systems analysis, structural analysis. The main purpose of these reflections is to find a multi-disciplinary approach which organizes knowledge, creates universal language design and controls complex sets. In fact, system analysis is structured sequentially by steps: the observation of the system by various observers in various aspects, the analysis of interactions and regulatory chains, the modeling that takes into account the evolution of the system, the simulation and the real tests in order to obtain the consensus. Thus the system approach allows two types of analysis according to the structure and the function of the system. The purpose of this paper is to present an application of system analysis of Unmanned Aerial Vehicle (UAV) components in order to represent the architecture of this system. Method: There are various analysis methods which are proposed, in the literature, in to carry out actions of global analysis and different points of view as SADT method (Structured Analysis and Design Technique), Petri Network. The methodology adopted in order to contribute to the system analysis of an Unmanned Aerial Vehicle has been proposed in this paper and it is based on the use of SADT. In fact, we present a functional analysis based on the SADT method of UAV components Body, power supply and platform, computing, sensors, actuators, software, loop principles, flight controls and communications). Results: In this part, we present the application of SADT method for the functional analysis of the UAV components. This SADT model will be composed exclusively of actigrams. It starts with the main function ‘To analysis of the UAV components’. Then, this function is broken into sub-functions and this process is developed until the last decomposition level has been reached (levels A1, A2, A3 and A4). Recall that SADT techniques are semi-formal; however, for the same subject, different correct models can be built without having to know with certitude which model is the good or, at least, the best. In fact, this kind of model allows users a sufficient freedom in its construction and so the subjective factor introduces a supplementary dimension for its validation. That is why the validation step on the whole necessitates the confrontation of different points of views. Conclusion: In this paper, we presented an application of system analysis of Unmanned Aerial Vehicle components. In fact, this application of system analysis is based on SADT method (Structured Analysis Design Technique). This functional analysis proved the useful use of SADT method and its ability of describing complex dynamic systems.

Keywords: system analysis, unmanned aerial vehicle, functional analysis, architecture

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Authors: Julia A. Ermakova

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As a member of a multicultural society, it is imperative that individuals demonstrate the highest level of decorum in order to exemplify the beauty of their culture. Adab, the practice of praiseworthy words and deeds, as well as possessing good manners and pursuing that which is considered good, is a fundamental concept that guards against all types of mistakes. In Islam, etiquette for every situation in life is taught, and it constitutes the way of life for a Muslim. In light of this, the personality of an elegant Muslim woman can be described as one who embodies the following qualities: Firstly, cultural speech and erudition are essential components. Improving one's intellect, learning new things, reading diverse literature, expanding one's vocabulary, working on articulation, and avoiding obscene speech and verbosity are crucial. Additionally, listening more than speaking and being willing to discuss one's culture when asked are commendable qualities. Conversely, it is important to avoid discussing foolish matters with foolish people and to be able to respond appropriately and change the subject if someone attempts to hurt or manipulate. Secondly, the style of speech is also of paramount importance. It is recommended to speak in a measured tone with a quiet voice and deep breathing. Avoiding rushing and shortness of breath is also recommended. Thirdly, awareness of how to greet others is essential. Combining Shariah and small talk etiquette, such as making a gesture of respect by putting one's hand to the chest and smiling slightly when a man offers a handshake, is recommended. Understanding the rules of small talk, taboo topics, and self-presentation is also important. Fourthly, knowing how to give and receive compliments without devaluing them is imperative. Knowledge of the rules of good manners and etiquette, both secular and Shariah, is also essential. Fifthly, avoiding arguments and responding elegantly to rudeness and tactlessness is a sign of an elegant Muslim woman. Treating everyone with respect and avoiding prejudices, taboo topics, inappropriate questions, and bad habits are all aspects of politeness. Sixthly, a neat appearance appropriate to Shariah and the local community, as well as a well-put-together outfit with a touch of elegance and style, are crucial. Posture, graceful movement, and a pleasant gaze are also important. Finally, good spirits and inner calm are key to projecting a harmonious image, which encourages people to listen attentively. Giving thanks to Allah in every situation in life is the key to maintaining good spirits. In conclusion, an elegant Muslim woman in a multicultural society is characterized by her high moral qualities and adherence to Islamic etiquette. These qualities, such as cultural speech and erudition, style of speech, awareness of how to greet, knowledge of good manners and etiquette, avoiding arguments, politeness, a neat appearance, and good spirits, all contribute to projecting an image of elegance and respectability. By exemplifying these qualities, Muslim women can serve as positive ambassadors for their culture and religion in diverse societies.

Keywords: adab, elegance, muslim woman, multicultural societies, good manners, etiquette

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Authors: Mobarok Hossain Bhuyain

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Video surveillance processing has attracted various security fields transforming it into one of the leading research fields. Today's demand for detection and tracking of human mobility for security is very useful for human security, such as in crowded areas. Accordingly, video surveillance technology has seen a rapid advancement in recent years, with algorithms analyzing the behavior of people under surveillance automatically. The main motivation of this research focuses on the detection and tracking of the elderly and socially vulnerable people in crowded areas. Degenerate people are a major health concern, especially for elderly people and socially vulnerable people. One major disadvantage of video surveillance is the need for continuous monitoring, especially in crowded areas. To assist the security monitoring live surveillance video, image processing, and artificial intelligence methods can be used to automatically send warning signals to the monitoring officers about elderly people and socially vulnerable people.

Keywords: human detection, target tracking, neural network, particle filter

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Authors: Giorgia Zotti

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This research comprehensively investigates the multifaceted interplay determining school performance, individual backgrounds, and regional disparities within the landscape of Italian secondary education. Leveraging data gleaned from the INVALSI 2021-2022 database, the analysis meticulously scrutinizes two fundamental distributions of educational achievements: the standardized Invalsi test scores and official grades in Italian and Mathematics, focusing specifically on final-year secondary school students in Italy. Applying a comprehensive methodology, the study initially employs Data Envelopment Analysis (DEA) to assess school performances. This methodology involves constructing a production function encompassing inputs (hours spent at school) and outputs (Invalsi scores in Italian and Mathematics, along with official grades in Italian and Math). The DEA approach is applied in both of its versions: traditional and conditional. The latter incorporates environmental variables such as school type, size, demographics, technological resources, and socio-economic indicators. Additionally, the analysis delves into regional disparities by leveraging the Theil Index, providing insights into disparities within and between regions. Moreover, in the frame of the inequality of opportunity theory, the study quantifies the inequality of opportunity in students' educational achievements. The methodology applied is the Parametric Approach in the ex-ante version, considering diverse circumstances like parental education and occupation, gender, school region, birthplace, and language spoken at home. Consequently, a Shapley decomposition is applied to understand how much each circumstance affects the outcomes. The outcomes of this comprehensive investigation unveil pivotal determinants of school performance, notably highlighting the influence of school type (Liceo) and socioeconomic status. The research unveils regional disparities, elucidating instances where specific schools outperform others in official grades compared to Invalsi scores, shedding light on the intricate nature of regional educational inequalities. Furthermore, it emphasizes a heightened inequality of opportunity within the distribution of Invalsi test scores in contrast to official grades, underscoring pronounced disparities at the student level. This analysis provides insights for policymakers, educators, and stakeholders, fostering a nuanced understanding of the complexities within Italian secondary education.

Keywords: inequality, education, efficiency, DEA approach

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Authors: Mohammed M. Siddeq, Mohammed H. Rasheed, Omar M. Salih, Marcos A. Rodrigues

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This research proposes a data encoding and decoding method based on the Matrix Minimization algorithm. This algorithm is applied to high-frequency coefficients for compression/encoding. The algorithm starts by converting every three coefficients to a single value; this is accomplished based on three different keys. The decoding/decompression uses a search method called QSS (Quick Sequential Search) Decoding Algorithm presented in this research based on the sequential search to recover the exact coefficients. In the next step, the decoded data are saved in an auxiliary array. The basic idea behind the auxiliary array is to save all possible decoded coefficients; this is because another algorithm, such as conventional sequential search, could retrieve encoded/compressed data independently from the proposed algorithm. The experimental results showed that our proposed decoding algorithm retrieves original data faster than conventional sequential search algorithms.

Keywords: matrix minimization algorithm, decoding sequential search algorithm, image compression, DCT, DWT

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Authors: Lavanya Madhuri Bollipo, K. V. Kadambari

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Objective: To discuss key issues in the diagnosis of Parkinson disease (PD), To discuss features influencing PD progression, To discuss importance of brain SPECT data in PD diagnosis, and To discuss the essentiality of machine learning techniques in early diagnosis of PD. An accurate and early diagnosis of PD is nowadays a challenge as clinical symptoms in PD arise only when there is more than 60% loss of dopaminergic neurons. So far there are no laboratory tests for the diagnosis of PD, causing a high rate of misdiagnosis especially when the disease is in the early stages. Recent neuroimaging studies with brain SPECT using 123I-Ioflupane (DaTSCAN) as radiotracer shown to be widely used to assist the diagnosis of PD even in its early stages. Machine learning techniques can be used in combination with image analysis procedures to develop computer-aided diagnosis (CAD) systems for PD. This paper addressed recent studies involving diagnosis of PD in its early stages using brain SPECT data with Machine Learning Techniques.

Keywords: Parkinson disease (PD), dopamine transporter, single-photon emission computed tomography (SPECT), support vector machine (SVM)

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Authors: Sabine Ambros, Ulrich Kulozik

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Berries such as blue- and raspberries belong to the most valuable fruits. To preserve the characteristic flavor and the high contents of vitamins and anthocyanins, the very sensitive berries are usually dried by lyophilization. As this method is very time- and energy-consuming, the dried fruit is extremely expensive. However, healthy snack foods are growing in popularity. Especially dried fruit free of any additives or additional sugar are more and more asked for. To make these products affordable, the fruits have to be dried by a method that is more energy-efficient than freeze drying but reveals the same high product quality. The additional insertion of microwaves to a freeze drying process was examined in this work to overcome the inconveniences of freeze drying. As microwaves penetrate the product volumetrically, sublimation takes place simultaneously all over the product and leads to a many times shorter process duration. A range of microwave and pressure settings was applied to find the optimum drying condition. The influence of the process parameters microwave power and chamber pressure on drying kinetics, product temperature and product quality was investigated to find the best condition for an energy-efficient process with high product quality. The product quality was evaluated by rehydration capacitiy, crispiness, shrinkage, color, vitamin C content and antioxidative capacity. The conclusion could be drawn that microwave freeze dried berries were almost equal to freeze dried fruit in all measured quality parameters or even could overcome it. Additionally, sensory evaluations could confirm the analytical studies. Drying time could be reduced by more than 75% at much lower energy consumption rates. Thus, an energy-efficient and cost saving method compared to the conventional freeze drying technique for the gentle production of tasty fruit or vegetable snacks has been found. This technique will make dried high-quality snacks available for many of consumers.

Keywords: blueberries, freeze drying, microwave freeze drying, process parameters, product quality

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Authors: Varsha Singh, Shraddha Prajapati, M. B. Kiran

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Texture identification is useful in predicting the functionality of a component. Many of the existing texture identification methods are of contact in nature, which limits its measuring speed. These contact measurement techniques use a diamond stylus and the diamond stylus being sharp going to damage the surface under inspection and hence these techniques can be used in statistical sampling. Though these contact methods are very accurate, they do not give complete information for full characterization of surface. In this context, the presented method assumes special significance. The method uses a relatively low cost vision system for image acquisition. Software is developed based on wavelet transform, for analyzing texture images. Specimens are made using different manufacturing process (shaping, grinding, milling etc.) During experimentation, the specimens are illuminated using proper lighting and texture images a capture using CCD camera connected to the vision system. The software installed in the vision system processes these images and subsequently identify the texture of manufacturing processes.

Keywords: diamond stylus, manufacturing process, texture identification, vision system

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Authors: Pelin Yılmaz Çetiner, Metin Mert İlgün, Nazlı Çetindağ, Emine Birci, Gizemnur Yıldız Uysal, Özcan Hatipoğlu, Ehsan Tuzcuoğlu, Gökhan Sır

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Water scarcity is an inevitable problem affecting more and more people day by day. It is a worldwide crisis and a consequence of rapid population growth, urbanization and overexploitation. Thus, the solutions providing the reclamation of the wastewater are the desired approach. Wastewater contains various substances such as organic, soaps and detergents, solvents, biological substances, and inorganic substances. The physical properties of the wastewater differs regarding to its origin such as commerical, domestic or hospital usage. Thus, the treatment strategy of this type of wastewater is should be comprehensively investigated and properly treated. The advanced oxidation process comes up as a hopeful method associated with the formation of reactive hydroxyl radicals that are highly reactive to oxidize of organic pollutants. This process has a priority on other methods such as coagulation, flocuation, sedimentation and filtration since it was not cause any undesirable by-products. In the present study, it was aimed to investigate the applicability of advanced oxidation process for the treatment of household appliances wastewater. For this purpose, the laboratory studies providing the effectively addressing of the formed radicals to organic pollutants were carried out. Then the effect of process parameters were comprehensively studied by using response surface methodology, Box-Benhken experimental desing. The final chemical oxygen demand (COD) was the main output to evaluate the optimum point providing the expected COD removal. The linear alkyl benzene sulfonate (LAS), total dissolved solids (TDS) and color were measured for the optimum point providing the expected COD removal. Finally, present study pointed out that advanced oxidation process might be efficiently preffered to treat of the household appliances wastewater and the optimum process parameters provided that expected removal of COD.

Keywords: advanced oxidation process, household appliances wastewater, modelling, water reuse

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Authors: L. Bernabeo, T. Loftus

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Many children often experience phases of picky eating, food aversions and/or avoidance. For families with children who have special needs, these experiences are often exacerbated, which can lead to feelings that negatively impact a caregiver’s relationship with their child. Within the scope of speech language pathology practice, knowledge of both emotional and feeding development is key. This paper will explore the significance of “messy play” within typical feeding development, and the challenges that may arise if a child does not have the opportunity to engage in this type of exploratory play. This paper will consider several contributing factors that can result in a “picky eater.” Further, research has shown that individuals with special needs, including autism, possess a neurological makeup that differs from that of a typical individual. Because autism is a disorder of relating and communicating due to differences in the limbic system, an individual with special needs may respond to a typical feeding experience as if it is a traumatic event. As a result, broadening one’s dietary repertoire may seem to be an insurmountable challenge. This paper suggests that introducing new foods through exploratory play can help broaden and strengthen diets, as well as improve the feeding experience, of individuals with autism. The DIRFloortimeⓇ methodology stresses the importance of following a child's lead. Within this developmental model, there is a special focus on a person’s individual differences, including the unique way they process the world around them, as well as the significance of therapy occurring within the context of a strong and motivating relationship. Using this child-centered approach, we can support our children in expanding their diets, while simultaneously building upon their cognitive and creative development through playful and respectful interactions that include exposure to foods that differ in color, texture, and smell. Further, this paper explores the importance of exploration, self-feeding and messy play on brain development, both in the context of typically developing individuals and those with disordered development.

Keywords: development, feeding, floortime, sensory

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Authors: Andrea J. Kirk-Jenkins

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Women in late adolescence and young adulthood are particularly vulnerable to disordered eating, and prior research indicates that those within the college and sorority communities may be especially susceptible. Research has primarily involved comparing eating disorder symptoms between sorority women and non-sorority members using formal eating disorder assessments. This phenomenological study examined sorority members’ (N = 10) perceptions of and lived experiences with various disordered eating behaviors within the sorority culture. Data from individual interviews and photographs indicated two structural themes and 11 textural themes related to factors associated with disordered eating behaviors. These findings point to the existence of both positive and negative aspects of sorority culture, normalization of disordered eating behaviors, and pressure to attain or maintain an ideal body image. Implications for university stakeholders, including college counselors, health center staff, and extracurricular program leaders, are discussed. Further research on the identified textural themes as well as a longitudinal study exploring how perceptions change from rush to alumnae status is suggested.

Keywords: eating disorders, disorder eating behaviors, sorority women, sorority culture, college women

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Authors: Elisa K. Schoenell, Cristiano De Oliveira, Luiz R. H. Dos Santos, Alexandre Giacobbo, Andréa M. Bernardes, Marco A. S. Rodrigues

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Water is an indispensable natural resource, which must be preserved to human activities as well the ecosystems. However, the sewage discharge has been contaminating water resources. Conventional treatment, such as physicochemical treatment followed by biological processes, has not been efficient to the complete degradation of persistent organic compounds, such as medicines and hormones. Therefore, the use of advanced technologies to sewage treatment has become urgent and necessary. The aim of this study was to apply Reverse Osmosis (RO) on sewage tertiary treatment from a Waste Water Treatment Plant (WWTP) in south Brazil. It was collected 200 L of sewage pre-treated by wetland with aquatic macrophytes. The sewage was treated in a RO pilot plant, using a polyamide membrane BW30-4040 model (DOW FILMTEC), with 7.2 m² membrane area. In order to avoid damage to the equipment, this system contains a pleated polyester filter with 5 µm pore size. It was applied 8 bar until achieve 5 times of concentration, obtaining 80% of recovery of permeate, with 10 L.min-1 of concentrate flow rate. Samples of sewage pre-treated on WWTP, permeate and concentrate generated on RO was analyzed for physicochemical parameters and by gas chromatography (GC) to qualitative analysis of organic compounds. The results proved that the sewage treated on WWTP does not comply with the limit of phosphorus and nitrogen of Brazilian legislation. Besides this, it was found many organic compounds in this sewage, such as benzene, which is carcinogenic. Analyzing permeate results, it was verified that the RO as sewage tertiary treatment was efficient to remove of physicochemical parameters, achieving 100% of iron, copper, zinc and phosphorus removal, 98% of color removal, 91% of BOD and 62% of ammoniacal nitrogen. RO was capable of removing organic compounds, however, it was verified the presence of some organic compounds on de RO permeate, showing that RO did not have the capacity of removal all organic compounds of sewage. It has to be considered that permeate showed lower intensity of peaks in chromatogram in comparison to the sewage of WWTP. It is important to note that the concentrate generate on RO needs a treatment before its disposal in environment.

Keywords: organic compounds, reverse osmosis, sewage treatment, tertiary treatment

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Authors: Alexander Hudson, Shaogang Gong

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Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

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Authors: Richard, Iyan Subiyanto, Chairul Hudaya

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Activated carbon has been playing a significant role for many applications, especially in energy storage devices. However, commercially activated carbons generally require complicated processes and high production costs. Therefore, in this study, an activated carbon originating from green coke waste, that is economically affordable will be used as a carbon source. To synthesize activated carbon, KOH as an activator was employed with variation of C:KOH in ratio of 1:2, 1:3, 1:4, and 1:5, respectively, with an activation temperature of 700°C. The characterizations of activated carbon are obtained from Scanning Electron Microscopy, Energy Dispersive X-Ray, Raman Spectroscopy, and Brunauer-Emmett-Teller. The optimal activated carbon sample with specific surface area of 2,024 m²/g with high carbon content ( > 80%) supported by the high porosity carbon image obtained by SEM was prepared at C:KOH ratio of 1:4. The result shows that the synthesized activated carbon would be an ideal choice for energy storage device applications. Therefore, this study is expected to reduce the costs of activated carbon production by expanding the utilization of petroleum waste.

Keywords: activated carbon, energy storage material, green coke, specific surface area

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Authors: Zahra Soleimani Rad, Fariborz Masoudi, Shirin Tondkar

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Turquoise is one of the most well-known gemstones in Iran. The mineralogy, crystallography, and gemology of Shahr-e-Babak turquoise in Kerman were investigated and the results are presented in this research. The Miduk porphyry copper deposit is positioned in the Shahr-Babak area in Kerman province, Iran. This deposit is located 85 km NW of the Sar-Cheshmeh porphyry copper deposit. Preliminary mineral exploration was carried out from 1967 to 1970. So far, more than fifty diamond drill holes, each reaching a maximum depth of 1013 meters, have provided evidence supporting the presence of significant and promising porphyry copper mineralization at the Miduk deposit. The mineral deposit harbors a quantity of 170 million metric tons of ore, characterized by a mean composition of 0.86% copper (Cu), 0.007% molybdenum (Mo), 82 parts-per-billion gold (Au), and 1.8 parts-per-million silver (Ag). The Supergene enrichment layer, which constitutes the predominant source of copper ore, exhibits an approximate thickness of 50 meters. Petrography shows that the texture is homogeneous. In terms of a gemstone, greasy luster and blue color are seen, and samples are similar to what is commonly known as turquoise. The geometric minerals were detected in XRD analysis by analyzing the data using the x-pert software. From the mineralogical point of view; the turquoise gemstones of Miduk of Kerman consist of turquoise, quartz, mica, and hübnerite. In this article, to our best knowledge, we are stating the hübnerite mineral identified and seen in the Persian turquoise. Based on the obtained spectra, the main mineral of the Miduk samples from the six members of the turquoise family is the turquoise type with identical peaks that can be used as a reference for identification of the Miduk turquoise. This mineral is structurally composed of phosphate units, units of Al, Cu, water, and hydroxyl units, and does not include a Fe unit. In terms of gemology, the quality of a gemstone depends on the quantity of the turquoise phase and the amount of Cu in it according to SEM and XRD analysis.

Keywords: turquoise, hübnerite, XRD analysis, Miduk, Kerman, Iran

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Authors: Rania Ahmed Kadry Abdel Gawad Birry, Mohamed El-Habrouk

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This paper presents a brief survey of the techniques used for sign language recognition along with the types of sensors used to perform the task. It presents a modified method for identification of an isolated sign language gesture using Microsoft Kinect with the OpenNI framework. It presents the way of extracting robust features from the depth image provided by Microsoft Kinect and the OpenNI interface and to use them in creating a robust and accurate gesture recognition system, for the purpose of ASL translation. The Prime Sense’s Natural Interaction Technology for End-user - NITE™ - was also used in the C++ implementation of the system. The algorithm presents a simple finger counting algorithm for static signs as well as directional Finite State Machine (FSM) description of the hand motion in order to help in translating a sign language gesture. This includes both letters and numbers performed by a user, which in-turn may be used as an input for voice pronunciation systems.

Keywords: American sign language, finger counting, hand tracking, Microsoft Kinect

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Authors: Sunglim Lee, Susumu Fujii, Koji Okamura

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Smart grid is a new approach for electric power grid that uses information and communications technology to control the electric power grid. Smart grid provides real-time control of the electric power grid, controlling the direction of power flow or time of the flow. Control devices are installed on the power lines of the electric power grid to implement smart grid. The number of the control devices should be determined, in relation with the area one control device covers and the cost associated with the control devices. One approach to determine the number of the control devices is to use the data on the surplus power generated by home solar generators. In current implementations, the surplus power is sent all the way to the power plant, which may cause power loss. To reduce the power loss, the surplus power may be sent to a control device and sent to where the power is needed from the control device. Under assumption that the control devices are installed on a lattice of equal size squares, our goal is to figure out the optimal spacing between the control devices, where the power sharing area (the area covered by one control device) is kept small to avoid power loss, and at the same time the power sharing area is big enough to have no surplus power wasted. To achieve this goal, a simulation using landscape ecology method is conducted on a sample area. First an aerial photograph of the land of interest is turned into a mosaic map where each area is colored according to the ratio of the amount of power production to the amount of power consumption in the area. The amount of power consumption is estimated according to the characteristics of the buildings in the area. The power production is calculated by the sum of the area of the roofs shown in the aerial photograph and assuming that solar panels are installed on all the roofs. The mosaic map is colored in three colors, each color representing producer, consumer, and neither. We started with a mosaic map with 100 m grid size, and the grid size is grown until there is no red grid. One control device is installed on each grid, so that the grid is the area which the control device covers. As the result of this simulation we got 350 m as the optimal spacing between the control devices that makes effective use of the surplus power for the sample area.

Keywords: landscape ecology, IT, smart grid, aerial photograph, simulation

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Authors: Manuel Alejandro Taborda Ceballos, Martin Sommerfeld

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Transport phenomena and dispersion of non-spherical particle in turbulent flows are found everywhere in industrial application and processes. Powder handling, pollution control, pneumatic transport, particle separation are just some examples where the particle encountered are not only spherical. These types of multiphase flows are wall bounded and mostly highly turbulent. The particles found in these processes are rarely spherical but may have various shapes (e.g., fibers, and rods). Although research related to the behavior of regular non-spherical particles in turbulent flows has been carried out for many years, it is still necessary to refine models, especially near walls where the interaction fiber-wall changes completely its behavior. Imaging-based experimental studies on dispersed particle-laden flows have been applied for many decades for a detailed experimental analysis. These techniques have the advantages that they provide field information in two or three dimensions, but have a lower temporal resolution compared to point-wise techniques such as PDA (phase-Doppler anemometry) and derivations therefrom. The applied imaging techniques in dispersed two-phase flows are extensions from classical PIV (particle image velocimetry) and PTV (particle tracking velocimetry) and the main emphasis was simultaneous measurement of the velocity fields of both phases. In a similar way, such data should also provide adequate information for validating the proposed models. Available experimental studies on the behavior of non-spherical particles are uncommon and mostly based on planar light-sheet measurements. Especially for elongated non-spherical particles, however, three-dimensional measurements are needed to fully describe their motion and to provide sufficient information for validation of numerical computations. For further providing detailed experimental results allowing a validation of numerical calculations of non-spherical particle dispersion in turbulent flows, a water channel test facility was built around a horizontal closed water channel. Into this horizontal main flow, a small cross-jet laden with fiber-like particles was injected, which was also solely driven by gravity. The dispersion of the fibers was measured by applying imaging techniques based on a LED array for backlighting and high-speed cameras. For obtaining the fluid velocity fields, almost neutrally buoyant tracer was used. The discrimination between tracer and fibers was done based on image size which was also the basis to determine fiber orientation with respect to the inertial coordinate system. The synchronous measurement of fluid velocity and fiber properties also allow the collection of statistics of fiber orientation, velocity fields of tracer and fibers, the angular velocity of the fibers and the orientation between fiber and instantaneous relative velocity. Consequently, an experimental study the behavior of elongated non-spherical particles in wall bounded turbulent flows was achieved. The development of a comprehensive analysis was succeeded, especially near the wall region, where exists hydrodynamic wall interaction effects (e.g., collision or lubrication) and abrupt changes of particle rotational velocity. This allowed us to predict numerically afterwards the behavior of non-spherical particles within the frame of the Euler/Lagrange approach, where the particles are therein treated as “point-particles”.

Keywords: crossflow, non-spherical particles, particle tracking velocimetry, PIV

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Authors: Aarushi Agarwal, Tara Singh, Anju Lata Singh, Trayambak Tiwari, Indramani Lal Singh

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The existing interdependent relationship between attention and consciousness has been put to debate since long. To testify the nature, dual-task paradigm has been used to simultaneously manipulate awareness and attention. With central discrimination task which is attentional demanding, participants also perform simple discrimination task in the periphery in near absence of attention. Individual-based analysis of performance accuracy in single and dual condition showed and above chance level performance i.e. more than 80%. In order to widen the understanding of extent of discrimination carried in near absence of attention, natural image and its geometric equivalent shape were presented in the periphery; synthetic objects accounted to lower level of performance than natural objects in dual condition. The gaze plot and heatmap indicate that peripheral performance do not necessarily involve saccade every time, verifying the discrimination in the periphery was in near absence of attention. Thus our studies show an interdependent nature of attention and awareness.

Keywords: attention, awareness, dual task paradigm, natural and geometric images

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Authors: Rohit T. P., Sahil Athrij, Sasi Gopalan

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Currently, the content entertainment industry is dominated by mobile devices. As the trends slowly shift towards Augmented/Virtual Reality applications the computational demands on these devices are increasing exponentially and we are already reaching the limits of hardware optimizations. This paper proposes a software solution to this problem. By leveraging the capabilities of cloud computing we can offload the work from mobile devices to dedicated rendering servers that are way more powerful. But this introduces the problem of latency. This paper introduces a protocol that can achieve high-performance low latency Augmented/Virtual Reality experience. There are two parts to the protocol, 1) In-flight compression The main cause of latency in the system is the time required to transmit the camera frame from client to server. The round trip time is directly proportional to the amount of data transmitted. This can therefore be reduced by compressing the frames before sending. Using some standard compression algorithms like JPEG can result in minor size reduction only. Since the images to be compressed are consecutive camera frames there won't be a lot of changes between two consecutive images. So inter-frame compression is preferred. Inter-frame compression can be implemented efficiently using WebGL but the implementation of WebGL limits the precision of floating point numbers to 16bit in most devices. This can introduce noise to the image due to rounding errors, which will add up eventually. This can be solved using an improved interframe compression algorithm. The algorithm detects changes between frames and reuses unchanged pixels from the previous frame. This eliminates the need for floating point subtraction thereby cutting down on noise. The change detection is also improved drastically by taking the weighted average difference of pixels instead of the absolute difference. The kernel weights for this comparison can be fine-tuned to match the type of image to be compressed. 2) Dynamic Load distribution Conventional cloud computing architectures work by offloading as much work as possible to the servers, but this approach can cause a hit on bandwidth and server costs. The most optimal solution is obtained when the device utilizes 100% of its resources and the rest is done by the server. The protocol balances the load between the server and the client by doing a fraction of the computing on the device depending on the power of the device and network conditions. The protocol will be responsible for dynamically partitioning the tasks. Special flags will be used to communicate the workload fraction between the client and the server and will be updated in a constant interval of time ( or frames ). The whole of the protocol is designed so that it can be client agnostic. Flags are available to the client for resetting the frame, indicating latency, switching mode, etc. The server can react to client-side changes on the fly and adapt accordingly by switching to different pipelines. The server is designed to effectively spread the load and thereby scale horizontally. This is achieved by isolating client connections into different processes.

Keywords: 2D kernelling, augmented reality, cloud computing, dynamic load distribution, immersive experience, mobile computing, motion tracking, protocols, real-time systems, web-based augmented reality application

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Authors: Hamed Kalhori, Lin Ye

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In this study, an inverse method was developed to reconstruct the magnitude and duration of impact forces exerted to a rectangular carbon fibre-epoxy composite honeycomb sandwich panel. The dynamic signals captured by Piezoelectric (PZT) sensors installed on the panel remotely from the impact locations were utilized to reconstruct the impact force generated by an instrumented hammer through an extended deconvolution approach. Two discretized forms of convolution integral are considered; the traditional one with an explicit transfer function and the modified one without an explicit transfer function. Deconvolution, usually applied to reconstruct the time history (e.g. magnitude) of a stochastic force at a defined location, is extended to identify both the location and magnitude of the impact force among a number of potential impact locations. It is assumed that a number of impact forces are simultaneously exerted to all potential locations, but the magnitude of all forces except one is zero, implicating that the impact occurs only at one location. The extended deconvolution is then applied to determine the magnitude as well as location (among the potential ones), incorporating the linear superposition of responses resulted from impact at each potential location. The problem can be categorized into under-determined (the number of sensors is less than that of impact locations), even-determined (the number of sensors equals that of impact locations), or over-determined (the number of sensors is greater than that of impact locations) cases. For an under-determined case, it comprises three potential impact locations and one PZT sensor for the rectangular carbon fibre-epoxy composite honeycomb sandwich panel. Assessments are conducted to evaluate the factors affecting the precision of the reconstructed force. Truncated Singular Value Decomposition (TSVD) and the Tikhonov regularization are independently chosen to regularize the problem to find the most suitable method for this system. The selection of optimal value of the regularization parameter is investigated through L-curve and Generalized Cross Validation (GCV) methods. In addition, the effect of different width of signal windows on the reconstructed force is examined. It is observed that the impact force generated by the instrumented impact hammer is sensitive to the impact locations of the structure, having a shape from a simple half-sine to a complicated one. The accuracy of the reconstructed impact force is evaluated using the correlation co-efficient between the reconstructed force and the actual one. Based on this criterion, it is concluded that the forces reconstructed by using the extended deconvolution without an explicit transfer function together with Tikhonov regularization match well with the actual forces in terms of magnitude and duration.

Keywords: honeycomb composite panel, deconvolution, impact localization, force reconstruction

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Authors: Viktorija Voidogaitė

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Catholic education is based on the belief that every human being is created in the image and likeness of God. It is also influenced by the idea that the Kingdom of Heaven belongs to the humble and vulnerable. These principles emphasize the importance of serving the most vulnerable members of the Church community and promoting inclusivity without discrimination. This perspective emphasizes the need to protect the weakest members with compassion. However, realizing such an ideal in practice proves challenging, as the shortcomings and errors prevalent in any society often stem from the actions of Christians within that society. The evolution of these connections is observed throughout the historical development of Catholic education. In some European countries, Catholic education has become elitist, with limited room for inclusivity. This creates a conspicuous gap between the principles of the Evangelical community and elite Catholic schools and gymnasiums. Some schools appear to be most inclined to educate only those students who best align with their profile, leaving those needing assistance on the margins. As we advance into the third decade of the 21st century, there emerges a fundamental consideration: whether individuals who can assist the underprivileged and the infirm are being emphasized. Yet, it remains an open question whether these individuals will also possess the willingness and capability to construct a community or society that is inclusive and accessible to all.

Keywords: inclusion, Catholic education, inclusive education, becoming

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: Samira Baghbanbari, A. B. P. Lever, Payam S. Shabestari, Donald Weaver

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Existing signal transmission models, although undoubtedly useful, have proven insufficient to explain the full complexity of information transfer within the central nervous system. The development of transformative models will necessitate a more comprehensive understanding of neuronal lipid membrane electrophysiology. Pursuant to this goal, the role of highly organized interfacial phospholipid-water layers emerges as a promising case study. A series of phospholipids in neural-glial gap junction interfaces as well as cholesterol molecules have been computationally modelled using high-performance density functional theory (DFT) calculations. Subsequent 'charge decomposition analysis' calculations have revealed a net transfer of charge from phospholipid orbitals through the organized interfacial water layer before ultimately finding its way to cholesterol acceptor molecules. The specific pathway of charge transfer from phospholipid via water layers towards cholesterol has been mapped in detail. Cholesterol is an essential membrane component that is overrepresented in neuronal membranes as compared to other mammalian cells; given this relative abundance, its apparent role as an electronic acceptor may prove to be a relevant factor in further signal transmission studies of the central nervous system. The timescales over which this electronic charge transfer occurs have also been evaluated by utilizing a system design that systematically increases the number of water molecules separating lipids and cholesterol. Memory loss through hydrogen-bonded networks in water can occur at femtosecond timescales, whereas existing action potential-based models are limited to micro or nanosecond scales. As such, the development of future models that attempt to explain faster timescale signal transmission in the central nervous system may benefit from our work, which provides additional information regarding fast timescale energy transfer mechanisms occurring through interfacial water. The study possesses a dataset that includes six distinct phospholipids and a collection of cholesterol. Ten optimized geometric characteristics (features) were employed to conduct binary classification through an artificial neural network (ANN), differentiating cholesterol from the various phospholipids. This stems from our understanding that all lipids within the first group function as electronic charge donors, while cholesterol serves as an electronic charge acceptor.

Keywords: charge transfer, signal transmission, phospholipids, water layers, ANN

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