Search results for: Hankel matrix

Authors: Ferhat Kadioglu

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A clamped-free vibrating beam technique was used to evaluate dynamic properties of glass fiber reinforced polymer matrix composite. In the experiment, an electromagnetic shaker and a non-contact laser head were used to vibrate and to take the response of the specimens, respectively. Test results showed that damping and elastic modulus of the material, as dynamic properties, could be obtained successfully using this technique. It was found that the balanced and symmetric specimens with 45 degrees are the best for damping performance. It is believed that such results could be used for the modal design of aerospace structures.

Keywords: composite materials, damping values, dynamic properties, non-contact measurements

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Authors: G. Imran, A. Pandurangan

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Epoxides constitute important intermediates for the production of fine and bulk chemicals as well as valuable building blocks for the synthesis of a variety of bioactive molecules. Manganese oxides are used as selective catalyst for various redox type reactions and also effectively used in the field of catalytic disposal of pollutants. Non-toxic, cost efficient factor and more over existence of wide range of oxidation state (+2 to +7) makes catalyst more interesting for both academic research and industrial applications. However, the serious drawback lying is the lower surface area. Exceedingly dispersed manganese oxide grafted over mesoporous solid material KIT-6 through ALD (Atomic Layer Deposition) technique effectively catalyze cyclohexene with H2O2 (30% in water) to corresponding epoxides. Highly selective epoxide >99% with 55.7% conversion of cyclohexene was achieved using huge dispersed active sites of MnOx species containing catalysts. Various weight percent such as (1, 3, 5, 7 & 10 wt %) of manganese (II) acetylacetonate complex was employed as Mn source to post-graft via active silanol groups of KIT-6 and are designated as (Mn-G-KIT-6). XRD, N2 sorption, HR-TEM, DRS-UV-VIS, EPR and H2-TPR were employed for structural and textural properties. Immense Mn species of about 95% proportion on silica matrix obtained was evident from ICP-OES.The resulting materials exhibited Type IV adsorption isotherms indiacting mesopore in nanorange. Si-KIT-6 and Mn-G-KIT-6 materials exhibited surface area of 519-289 m2/g and with decrease in pore volume of 0.96-0.49 cm3/g with pore diameter ranging 7.9- 7.2 with increase in wt%. DRS-UV-VIS spectroscopy and EPR studies reveal that manganese coexists as Mn2+/3+ species as extra-framework sites and frame-work sites that result in dispersion on surface of silica matrix of KIT-6 and incorporated manganese sites with silanol groups along with small sized MnO cluster, evident from HR-TEM which increase with Mn content. Conventional production of epoxides by the intramolecular etherification of chlorohydrins formed by the reaction of alkenes with hypochlorous acid is the major drawbacks obtained recently. The most efficient synthesis of oxiranes (epoxides) is obtained by mesoporous catalysts (Mn-G-KIT-6) are presented here and discussed.

Keywords: ALD, epoxidation, mesoporous, MnOx

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Authors: Mohd Shahneel Saharudin, Jiacheng Wei, Islam Shyha, Fawad Inam

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This study aimed to investigate the effect of aggressive environment on the flexural properties of halloysite nanotubes-polyester nanocomposites. Results showed that the addition of halloysite nanotubes into polyester matrix was found to improve flexural properties of the nanocomposites in dry condition and after water-methanol exposure. Significant increase in surface roughness was also observed and measured by Alicona Infinite Focus optical microscope.

Keywords: halloysite nanotube, composites, flexural properties, surface roughness

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Authors: Safak Isik, Ozalp Vayvay

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Strategic partnerships with suppliers play a vital role for the long-term value-based supply chain. This strategic collaboration keeps still being one of the top priority of many business organizations in order to create more additional value; benefiting mainly from supplier’s specialization, capacity and innovative power, securing supply and better managing costs and quality. However, many organizations encounter difficulties in initiating, developing and managing those partnerships and many attempts result in failures. One of the reasons for such failure is the incompatibility of members of this partnership or in other words wrong supplier selection which emphasize the significance of the selection process since it is the beginning stage. An effective selection process of strategic suppliers is critical to the success of the partnership. Although there are several research studies to select the suppliers in literature, only a few of them is related to strategic supplier selection for long-term partnership. The purpose of this study is to propose a conceptual model for the selection of strategic partnership suppliers. A two-stage approach has been used in proposed model incorporating first segmentation and second selection. In the first stage; considering the fact that not all suppliers are strategically equal and instead of a long list of potential suppliers, Kraljic’s purchasing portfolio matrix can be used for segmentation. This supplier segmentation is the process of categorizing suppliers based on a defined set of criteria in order to identify types of suppliers and determine potential suppliers for strategic partnership. In the second stage, from a pool of potential suppliers defined at first phase, a comprehensive evaluation and selection can be performed to finally define strategic suppliers considering various tangible and intangible criteria. Since a long-term relationship with strategic suppliers is anticipated, criteria should consider both current and future status of the supplier. Based on an extensive literature review; strategical, operational and organizational criteria have been determined and elaborated. The result of the selection can also be used to determine suppliers who are not ready for a partnership but to be developed for strategic partnership. Since the model is based on multiple criteria for both stages, it provides a framework for further utilization of Multi-Criteria Decision Making (MCDM) techniques. The model may also be applied to a wide range of industries and involve managerial features in business organizations.

Keywords: Kraljic’s matrix, purchasing portfolio, strategic supplier selection, supplier collaboration, supplier partnership, supplier segmentation

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Authors: Ahmet Karagoz, Irfan Karagoz

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Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.

Keywords: automatic target recognition, sparse representation, image classification, SAR images

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Authors: Lizeth Fuentes-Mera, Vanessa Perez-Silos, Nidia K. Moncada-Saucedo, Alejandro Garcia-Ruiz, Alberto Camacho, Jorge Lara-Arias, Ivan Marino-Martinez, Victor Romero-Diaz, Adolfo Soto-Dominguez, Humberto Rodriguez-Rocha, Hang Lin, Victor Pena-Martinez

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Biphasic scaffolds in cartilage tissue engineering have been designed to influence not only the recapitulation of the osteochondral architecture but also to take advantage of the healing ability of bone to promote the implant integration with the surrounding tissue and then bone restoration and cartilage regeneration. This study reports the development and characterization of a biphasic scaffold based on the assembly of a cartilage phase constituted by fibroin biofunctionalized with bovine cartilage matrix; cellularized with differentiated pre-chondrocytes from adipose tissue stem cells (autologous) and well attached to a bone phase (bone bovine decellularized) to mimic the structure of the nature of native tissue and to promote the cartilage regeneration in a model of joint damage in pigs. Biphasic scaffolds were assembled by fibroin crystallization with methanol. The histological and ultrastructural architectures were evaluated by optical and scanning electron microscopy respectively. Mechanical tests were conducted to evaluate Young's modulus of the implant. For the biological evaluation, pre-chondrocytes were loaded onto the scaffolds and cellular adhesion, proliferation, and gene expression analysis of cartilage extracellular matrix components was performed. The scaffolds that were cellularized and matured for 10 days were implanted into critical 3 mm in diameter and 9-mm in depth osteochondral defects in a porcine model (n=4). Three treatments were applied per knee: Group 1: monophasic cellular scaffold (MS) (single chondral phase), group 2: biphasic scaffold, cellularized only in the chondral phase (BS1), group 3: BS cellularized in both bone and chondral phases (BS2). Simultaneously, a control without treatment was evaluated. After 4 weeks of surgery, integration and regeneration tissues were analyzed by x-rays, histology and immunohistochemistry evaluation. The mechanical assessment showed that the acellular biphasic composites exhibited Young's modulus of 805.01 kPa similar to native cartilage (400-800 kPa). In vitro biological studies revealed the chondroinductive ability of the biphasic implant, evidenced by an increase in sulfated glycosaminoglycan (GAGs) and type II collagen, both secreted by the chondrocytes cultured on the scaffold during 28 days. No evidence of adverse or inflammatory reactions was observed in the in vivo trial; however, In group 1, the defects were not reconstructed. In group 2 and 3 a good integration of the implant with the surrounding tissue was observed. Defects in group 2 were fulfilled by hyaline cartilage and normal bone. Group 3 defects showed fibrous repair tissue. In conclusion; our findings demonstrated the efficacy of biphasic and bioactive scaffold based on silk fibroin, which entwined chondroinductive features and biomechanical capability with appropriate integration with the surrounding tissue, representing a promising alternative for osteochondral tissue-engineering applications.

Keywords: biphasic scaffold, extracellular cartilage matrix, silk fibroin, osteochondral tissue engineering

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Authors: Amirhosein Rostampour, Mehdi Sharif

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In this article, a series of high impact polystyrene/graphene (HIPS/Gr) nanocomposites were prepared by solution mixing method and their morphology and dynamic mechanical properties were investigated as a function of graphene content. SEM images and X-Ray diffraction data confirm that the graphene platelets are well dispersed in HIPS matrix for the nanocomposites with Gr contents up to 5.0 wt%. Mechanical properties analysis demonstrates that yielding strength and initial modulus of HIPS/Gr nanocomposites are highly improved with the increment of Gr content compared to pure HIPS.

Keywords: nanocomposite, graphene, dynamic mechanical properties, morphology

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Authors: Gamze Ozel, Selen Cakmakyapan

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We introduce a new model called the Marshall-Olkin Rayleigh distribution which extends the Rayleigh distribution using Marshall-Olkin transformation and has increasing and decreasing shapes for the hazard rate function. Various structural properties of the new distribution are derived including explicit expressions for the moments, generating and quantile function, some entropy measures, and order statistics are presented. The model parameters are estimated by the method of maximum likelihood and the observed information matrix is determined. The potentiality of the new model is illustrated by means of real life data set.

Keywords: Marshall-Olkin distribution, Rayleigh distribution, estimation, maximum likelihood

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Authors: Zeineb Yousse, Fakher Kharrat

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Mosaic is a part of a broad universal cultural heritage; sometimes it represents a rather essential source for the researches on the everyday life of some of the previous civilizations. Tunisia has one of the finest and largest collections of mosaics in the world, which is essentially exhibited in the Museums of Bardo and Sousse. Restored and reconstituted, they bear witnesses to hard work. Our paper deals with the discipline of conservation of Roman mosaics based on the proceedings of the workshop of the Museum of Sousse. Thus, we highlight two main objectives. In the first place, it is a question of revealing the techniques adopted by professionals to handle mosaics and to which school of conservation these techniques belong. In the second place, we are going to interpret the works initiated to preserve the archaeological heritage in order to protect it in present time and transmit it to future generations. To this end, we paid attention to four Roman mosaics currently exhibited in the Museum of Sousse. These Mosaics show different voids or gaps at the level of their surfaces and the method used to fill these gaps seems to be interesting to analyze. These mosaics are known under the names of: Orpheus Charming the Animals, Gladiator and Bears, Stud farm of Sorothus and finally Head of Medusa. The study on the conservation passes through two chained phases. We start with a small historical overview in order to gather information related to the original location, the date of its composition as well as the description of its image. Afterward, the intervention process is analyzed by handling three complementary elements which are: diagnosis of the existing state, the study of the medium processing and the study of the processing of the tesselatum surface which includes the pictorial composition of the mosaic. Furthermore, we have implemented an evaluation matrix with six operating principles allowing the assessment of the appropriateness of the intervention. These principles are the following: minimal intervention, reversibility, compatibility, visibility, durability, authenticity and enhancement. Various accumulated outcomes are pointing out the techniques used to fill the gaps as well as the level of compliance with the principles of conservation. Accordingly, the conservation of mosaics in Tunisia is a practice that combines various techniques without really arguing about the choice of a particular theory.

Keywords: conservation, matrix, museum of Sousse, operating particular theory, principles, Roman mosaics

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Authors: Muhammad Tahir Hassan, Stas Burek, Muhammad Asif, Mohamed Emad

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Industrial sector in Pakistan accounts for 25% of total energy consumption in the country. The performance of this sector has been severely affected due to the adverse effect of current energy crises in the country. Energy conservation potentials of Pakistan’s industrial sectors through energy management can save wasted energy which would ultimately leads to economic and environmental benefits. However due to lack of financial incentives of energy efficiency and absence of energy benchmarking within same industrial sectors are some of the main challenges in the implementation of energy management. In Pakistan, this area has not been adequately explored, and there is a lack of focus on the need for industrial energy efficiency and proper management. The main objective of this research is to evaluate the current energy management performance of Pakistani industrial sector and empirical investigation of the existence of various barriers to industrial energy efficiency. Data was collected from the respondents of 192 small and medium-sized enterprises (SME’s) of Pakistan i.e. foundries, textile, plastic industries, light engineering, auto and spare parts and ceramic manufacturers and analysed using Statistical Package for the Social Sciences (SPSS) software. Current energy management performance of manufacturing SME’s in Pakistan has been evaluated by employing two significant indicators, ‘Energy Management Matrix’ and ‘pay-off criteria’, with modified approach. Using the energy management matrix, energy management profiles of overall industry and the individual sectors have been drawn to assess the energy management performance and identify the weak and strong areas as well. Results reveal that, energy management practices in overall surveyed industries are at very low level. Energy management profiles drawn against each sector suggest that performance of textile sector is better among all the surveyed manufacturing SME’s. The empirical barriers to industrial energy efficiency have also been ranked according to the overall responses. The results further reveal that there is a significant relationship exists among the industrial size, sector type and nature of barriers to industrial energy efficiency for the manufacturing SME’s in Pakistan. The findings of this study may help the industries and policy makers in Pakistan to formulate a sustainable energy policy to support industrial energy efficiency keeping in view the actual existing energy efficiency scenario in the industrial sector.

Keywords: barriers, energy conservation, energy management profile, environment, manufacturing SME's of Pakistan

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Authors: Shih Yu Pan, Pao Chen Hung, Chuan Yao Lin, Charles C.-K. Chou, Yu Chi Lin, Kai Hsien Chi

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This study analyzed 16 atmospheric PAHs species which were controlled by USEPA and IARC. To measure the concentration of PAHs, four rural sampling sites and two urban sampling sites were selected in Central Taiwan during spring and summer. In central Taiwan, the rural sampling stations were located in the downstream of Da-An River, Da-Jang River, Wu River and Chuo-shui River. On the other hand, the urban sampling sites were located in Taichung district and close to the roadside. Ambient air samples of both vapor phase and particle phase of PAHs compounds were collected using high volume sampling trains (Analitica). The sampling media were polyurethane foam (PUF) with XAD2 and quartz fiber filters. Diagnostic ratio, Principal component analysis (PCA), Positive Matrix Factorization (PMF) models were used to evaluate the apportionment of PAHs in the atmosphere and speculate the relative contribution of various emission sources. Because of the high temperature and low wind speed, high PAHs concentration in the atmosphere was observed. The total PAHs concentration, especially in vapor phase, had significant change during summer. During the sampling periods the total PAHs concentration of atmospheric at four rural and two urban sampling sites in spring and summer were 3.70±0.40 ng/m3,3.40±0.63 ng/m3,5.22±1.24 ng/m3,7.23±0.37 ng/m3,7.46±2.36 ng/m3,6.21±0.55 ng/m3　; 15.0± 0.14 ng/m3,18.8±8.05 ng/m3,20.2±8.58 ng/m3,16.1±3.75 ng/m3,29.8±10.4 ng/m3,35.3±11.8 ng/m3, respectively. In order to identify PAHs sources, we used diagnostic ratio to classify the emission sources. The potential sources were diesel combustion and gasoline combustion in spring and summer, respectively. According to the principal component analysis (PCA), the PC1 and PC2 had 23.8%, 20.4% variance and 21.3%, 17.1% variance in spring and summer, respectively. Especially high molecular weight PAHs (BaP, IND, BghiP, Flu, Phe, Flt, Pyr) were dominated in spring when low molecular weight PAHs (AcPy, Ant, Acp, Flu) because of the dominating high temperatures were dominated in the summer. Analysis by using PMF model found the sources of PAHs in spring were stationary sources (34%), vehicle emissions (24%), coal combustion (23%) and petrochemical fuel gas (19%), while in summer the emission sources were petrochemical fuel gas (34%), the natural environment of volatile organic compounds (29%), coal combustion (19%) and stationary sources (18%).

Keywords: PAHs, source identification, diagnostic ratio, principal component analysis, positive matrix factorization

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Authors: Ali Isapour, Ramin Nateghi

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— Markov parameters are unique parameters of the system and remain unchanged under similarity transformations. Markov parameters from a power series that is convergent only if the system matrix’s eigenvalues are inside the unity circle. Therefore, Markov parameters of a stable discrete-time system are convergent. In this study, we aim to realize the system based on Markov parameters by using Artificial Neural Networks (ANN), and this end, we use Flexible Neural Networks. Realization means determining the elements of matrices A, B, C, and D.

Keywords: Markov parameters, realization, activation function, flexible neural network

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Authors: Eti Dwi Wiraningsih, Folashade Agusto, Lina Aryati, Syamsuddin Toaha, Suzanne Lenhart, Widodo, Willy Govaerts

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This paper considers a deterministic model for the transmission dynamics of rabies virus in the wild dogs-domestic dogs-human zoonotic cycle. The effect of vaccination and culling in dogs is considered on the model, then the stability was analysed to get basic reproduction number. We use the next generation matrix method and Routh-Hurwitz test to analyze the stability of the Disease-Free Equilibrium and Endemic Equilibrium of this model.

Keywords: stability analysis, rabies model, vaccination effect, culling in dogs

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Authors: Mohamed Mounir Tellache, Hiroyuki Kambara, Yasuharu Koike, Makoto Miyakoshi, Natsue Yoshimura

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This study explores the practicality of using electroencephalographic (EEG) independent components to predict eight-direction finger movements in pseudo-real-time. Six healthy participants with individual-head MRI images performed finger movements in eight directions with two different arm configurations. The analysis was performed in two stages. The first stage consisted of using independent component analysis (ICA) to separate the signals representing brain activity from non-brain activity signals and to obtain the unmixing matrix. The resulting independent components (ICs) were checked, and those reflecting brain-activity were selected. Finally, the time series of the selected ICs were used to predict eight finger-movement directions using Sparse Logistic Regression (SLR). The second stage consisted of using the previously obtained unmixing matrix, the selected ICs, and the model obtained by applying SLR to classify a different EEG dataset. This method was applied to two different settings, namely the single-participant level and the group-level. For the single-participant level, the EEG dataset used in the first stage and the EEG dataset used in the second stage originated from the same participant. For the group-level, the EEG datasets used in the first stage were constructed by temporally concatenating each combination without repetition of the EEG datasets of five participants out of six, whereas the EEG dataset used in the second stage originated from the remaining participants. The average test classification results across datasets (mean ± S.D.) were 38.62 ± 8.36% for the single-participant, which was significantly higher than the chance level (12.50 ± 0.01%), and 27.26 ± 4.39% for the group-level which was also significantly higher than the chance level (12.49% ± 0.01%). The classification accuracy within [–45°, 45°] of the true direction is 70.03 ± 8.14% for single-participant and 62.63 ± 6.07% for group-level which may be promising for some real-life applications. Clustering and contribution analyses further revealed the brain regions involved in finger movement and the temporal aspect of their contribution to the classification. These results showed the possibility of using the ICA-based method in combination with other methods to build a real-time system to control prostheses.

Keywords: brain-computer interface, electroencephalography, finger motion decoding, independent component analysis, pseudo real-time motion decoding

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Authors: Baba Mbaye

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In collaborative filtering recommendation systems, a user receives suggested items based on the opinions and evaluations of a community of users. This type of recommendation system uses only the information (notes in numerical values) contained in a usage matrix as input data. This matrix can be constructed based on users' behaviors or by offering users to declare their opinions on the items they know. The cold start problem leads to very poor performance for new users. It is a phenomenon that occurs at the beginning of use, in the situation where the system lacks data to make recommendations. There are three types of cold start problems: cold start for a new item, a new system, and a new user. We are interested in this article at the cold start for a new user. When the system welcomes a new user, the profile exists but does not have enough data, and its communities with other users profiles are still unknown. This leads to recommendations not adapted to the profile of the new user. In this paper, we propose an approach that improves cold start by using the notions of similarity and semantic proximity between users profiles during cold start. We will use the cold-metadata available (metadata extracted from the new user's data) useful in positioning the new user within a community. The aim is to look for similarities and semantic proximities with the old and current user profiles of the system. Proximity is represented by close concepts considered to belong to the same group, while similarity groups together elements that appear similar. Similarity and proximity are two close but not similar concepts. This similarity leads us to the construction of similarity which is based on: a) the concepts (properties, terms, instances) independent of ontology structure and, b) the simultaneous representation of the two concepts (relations, presence of terms in a document, simultaneous presence of the authorities). We propose an ontology, OIVCSRS (Ontology of Improvement Visitor Cold Start in Recommender Systems), in order to structure the terms and concepts representing the meaning of an information field, whether by the metadata of a namespace, or the elements of a knowledge domain. This approach allows us to automatically attach the new user to a user community, partially compensate for the data that was not initially provided and ultimately to associate a better first profile with the cold start. Thus, the aim of this paper is to propose an approach to improving cold start using semantic technologies.

Keywords: visitor cold start, recommender systems, collaborative filtering, semantic filtering

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Authors: Christopher Okechukwu Ndukwe

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This paper investigates and categorizes the flexural damage mechanisms in composite materials caused by mesoscopic out-of-plane buckle defects that occur during the initial stage of the resin transfer molding (RTM) process. The findings of this study have significant practical implications for the manufacturing and use of composite materials, as they provide a deeper understanding of these damage mechanisms and their analysis. During the initial stage of shaping a preform, alterations, and distortions in the reinforcement sample can significantly lead to defects, such as buckling, especially when forming double-curvature geometries. These recurring mesoscopic defects have been investigated using a specialized laboratory bench designed to reproduce buckle defects like those found in complex geometric shapes, such as tetrahedrons. The study examined two sample configurations with buckle defects in the longitudinal and transverse directions alongside a reference sample for comparison. An acoustic emission (AE) system, a well-regarded non-contact method for monitoring structural health, was used to analyze the mechanical behavior of material samples in detail. An unsupervised K-means algorithm was employed to classify the damage mechanisms—such as matrix cracking, interface damage, and fiber breakage linked to the samples' failure. A standard was established based on three AE parameters: absolute energy, amplitude, and the number of AE events. This standard helped identify the origin and sequence of damage propagation. Initially, the results of the AE parameters were superimposed with the flexural loading curves to pinpoint the loading phases during which damage began and the specific points at which the samples ultimately failed. The normalized density of AE events related to different damage mechanisms was evaluated by analyzing the number of AE events within the amplitude domain of the AE signals. The ranges of the identified damage mechanisms in the amplitude plane illustrate the progression and order of load transfer among the elements of the composite material. In the reference sample, the AE event signals corresponding to the three classes of damage mechanisms partially overlap with adjacent signals. In contrast, the two defective sample configurations showed that the overlapping AE event signals for the respective damage mechanisms converged within the intermediate damage mode area at specific points, depending on the sample configuration. The convergence points in the samples with transverse defects were identified relatively earlier than in the other samples. Low and high amplitude ranges characterize the matrix cracking and fiber breakage damage mechanisms. The low amplitude damage occurred over a more extended length, while the high amplitude damage began much earlier. This results in the signals from both damage mechanisms converging at the center of the interface damage zone. This convergence suggests that all individual composite components fail concurrently at specific points in the defective samples, resulting in rapid fragmentation and ultimately contributing to failure. Overall, the results show that mesoscopic out-of-plane buckling in all directions affects the composite's flexural response, with more severe effects observed when the load is applied transversely.

Keywords: acoustic emission, composite reinforcement, damage mechanisms, mesoscopic buckle defects

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Authors: N. A. Mokhtar, A. G. Hussin, Y. Z. Zubairi

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This paper proposes a new simultaneous simple linear functional relationship model by assuming equal error variances. We derive the maximum likelihood estimate of the parameters in the simultaneous model and the covariance. We show by simulation study the small bias values of the parameters suggest the suitability of the estimation method. As an illustration, the proposed simultaneous model is applied to real data of the wind direction and wave direction measured by two different instruments.

Keywords: simultaneous linear functional relationship model, Fisher information matrix, parameter estimation, circular variables

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Rawan Hakawati, Beatrice Smyth, David Rooney, Geoffrey McCullough

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Targets have been set in the EU to increase the share of renewable energy consumption to 20% by 2020, but developments have not occurred evenly across the member states. Northern Ireland is almost 90% dependent on imported fossil fuels. With such high energy dependency, Northern Ireland is particularly susceptible to the security of supply issues. Linked to fossil fuels are greenhouse gas emissions, and the EU plans to reduce emissions by 20% by 2020. The use of indigenously produced biomass could reduce both greenhouse gas emissions and external energy dependence. With a wide range of both crop and waste feedstock potentially available in Northern Ireland, anaerobic digestion has been put forward as a possible solution for renewable energy production, waste management, and greenhouse gas reduction. Not all feedstock, however, is the same, and an understanding of feedstock suitability is important for both plant operators and policy makers. The aim of this paper is to investigate biomass suitability for anaerobic digestion in Northern Ireland. It is also important that decisions are based on solid scientific evidence. For this reason, the methodology used is multi-criteria decision matrix analysis which takes multiple criteria into account simultaneously and ranks alternatives accordingly. The model uses the weighted sum method (which follows the Entropy Method to measure uncertainty using probability theory) to decide on weights. The Topsis method is utilized to carry out the mathematical analysis to provide the final scores. Feedstock that is currently available in Northern Ireland was classified into two categories: wastes (manure, sewage sludge and food waste) and energy crops, specifically grass silage. To select the most suitable feedstock, methane yield, feedstock availability, feedstock production cost, biogas production, calorific value, produced kilowatt-hours, dry matter content, and carbon to nitrogen ratio were assessed. The highest weight (0.249) corresponded to production cost reflecting a variation of £41 gate fee to 22£/tonne cost. The weights calculated found that grass silage was the most suitable feedstock. A sensitivity analysis was then conducted to investigate the impact of weights. The analysis used the Pugh Matrix Method which relies upon The Analytical Hierarchy Process and pairwise comparisons to determine a weighting for each criterion. The results showed that the highest weight (0.193) corresponded to biogas production indicating that grass silage and manure are the most suitable feedstock. Introducing co-digestion of two or more substrates can boost the biogas yield due to a synergistic effect induced by the feedstock to favor positive biological interactions. A further benefit of co-digesting manure is that the anaerobic digestion process also acts as a waste management strategy. From the research, it was concluded that energy from agricultural biomass is highly advantageous in Northern Ireland because it would increase the country's production of renewable energy, manage waste production, and would limit the production of greenhouse gases (current contribution from agriculture sector is 26%). Decision-making methods based on scientific evidence aid policy makers in classifying multiple criteria in a logical mathematical manner in order to reach a resolution.

Keywords: anaerobic digestion, biomass as feedstock, decision matrix, renewable energy

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Authors: Dagmara Malina, Katarzyna Bialik-Wąs, Klaudia Pluta

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The growing significance of transdermal systems, in which skin is a route for systemic drug delivery, has generated a considerable amount of data which has resulted in a deeper understanding of the mechanisms of transport across the skin in the context of the controlled and prolonged release of active substances. One of such solutions may be the use of carrier systems based on intelligent polymers with different physicochemical properties. In these systems, active substances, e.g. drugs, can be conjugated (attached), immobilized, or encapsulated in a polymer matrix that is sensitive to specific environmental conditions (e.g. pH or temperature changes). Intelligent polymers can be divided according to their sensitivity to specific environmental stimuli such as temperature, pH, light, electric, magnetic, sound, or electromagnetic fields. Materials & methods—The first stage of the presented research concerned the synthesis of pH-sensitive polymeric carriers by a radical polymerization reaction. Then, the selected active substance (hydrocortisone) was introduced into polymeric carriers. In a further stage, bio-hybrid sodium alginate/poly(vinyl alcohol) – SA/PVA-based hydrogel matrices modified with various carrier-drug systems were prepared with the chemical cross-linking method. The conducted research included the assessment of physicochemical properties of obtained materials i.e. degree of hydrogel swelling and degradation studies as a function of pH in distilled water and phosphate-buffered saline (PBS) at 37°C in time. The gel fraction represents the insoluble gel fraction as a result of inter-molecule cross-linking formation was also measured. Additionally, the chemical structure of obtained hydrogels was confirmed using FT-IR spectroscopic technique. The dynamic light scattering (DLS) technique was used for the analysis of the average particle size of polymer-carriers and carrier-drug systems. The nanocarriers morphology was observed using SEM microscopy. Results & Discussion—The analysis of the encapsulated polymeric carriers showed that it was possible to obtain the time-stable empty pH-sensitive carrier with an average size 479 nm and the encapsulated system containing hydrocortisone with an average 543 nm, which was introduced into hydrogel structure. Bio-hybrid hydrogel matrices are stable materials, and the presence of an additional component: pH-sensitive carrier – hydrocortisone system, does not reduce the degree of cross-linking of the matrix nor its swelling ability. Moreover, the results of swelling tests indicate that systems containing higher concentrations of the drug have a slightly higher sorption capacity in each of the media used. All analyzed materials show stable and statically changing swelling values in simulated body fluids - there is no sudden fluid uptake and no rapid release from the material. The analysis of FT-IR spectra confirms the chemical structure of the obtained bio-hybrid hydrogel matrices. In the case of modifications with a pH-sensitive carrier, a much more intense band can be observed in the 3200-3500 cm⁻¹ range, which most likely originates from the strong hydrogen interactions that occur between individual components.

Keywords: hydrogels, polymer nanocarriers, sodium alginate/poly(vinyl alcohol) matrices, wound dressings.

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Authors: Kushakov Kholmurodjon, Muhammadjonov Akbarshox

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This present paper is devoted to a system of second-order nonlinear differential equations with a special right-hand side, exactly, the linear part and a third-order polynomial of a special form. It is shown that for some relations between the parameters, there is a second-order curve in which trajectories leaving the points of this curve remain in the same place. Thus, the curve is invariant with respect to the given system. Moreover, this system is invariant under a non-degenerate linear transformation of variables. The form of this curve, depending on the relations between the parameters and the eigenvalues of the matrix, is proved. All solutions of this system of differential equations are shown analytically.

Keywords: dynamic system, ellipse, hyperbola, Hess system, polar coordinate system

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Authors: Jitendar Kumar Tiwari, Ajay Mandal, N. Sathish, A. K. Srivastava

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Since the last decade, graphene achieved great attention toward the progress of multifunction metal matrix composites, which are highly demanded in industries to develop energy-efficient systems. This study covers the two advanced aspects of the latest scientific endeavor, i.e., graphene as reinforcement in metallic materials and additive manufacturing (AM) as a processing technology. Herein, high-quality graphene and AlSi10Mg powder mechanically mixed by very low energy ball milling with 0.1 wt. % and 0.2 wt. % graphene. Mixed powder directly subjected to the powder bed fusion process, i.e., an AM technique to produce composite samples along with bare counterpart. The effects of graphene on porosity, microstructure, and mechanical properties were examined in this study. The volumetric distribution of pores was observed under X-ray computed tomography (CT). On the basis of relative density measurement by X-ray CT, it was observed that porosity increases after graphene addition, and pore morphology also transformed from spherical pores to enlarged flaky pores due to improper melting of composite powder. Furthermore, the microstructure suggests the grain refinement after graphene addition. The columnar grains were able to cross the melt pool boundaries in case of the bare sample, unlike composite samples. The smaller columnar grains were formed in composites due to heterogeneous nucleation by graphene platelets during solidification. The tensile properties get affected due to induced porosity irrespective of graphene reinforcement. The optimized tensile properties were achieved at 0.1 wt. % graphene. The increment in yield strength and ultimate tensile strength was 22% and 10%, respectively, for 0.1 wt. % graphene reinforced sample in comparison to bare counterpart while elongation decreases 20% for the same sample. The hardness indentations were taken mostly on the solid region in order to avoid the collapse of the pores. The hardness of the composite was increased progressively with graphene content. Around 30% of increment in hardness was achieved after the addition of 0.2 wt. % graphene. Therefore, it can be concluded that powder bed fusion can be adopted as a suitable technique to develop graphene reinforced AlSi10Mg composite. Though, some further process modification required to avoid the induced porosity after the addition of graphene, which can be addressed in future work.

Keywords: graphene, hardness, porosity, powder bed fusion, tensile properties

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Authors: A. Mimaroglu, H. Unal

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In this study, the mechanical properties of nano filled epoxy composites were evaluated. The matrix material is epoxy. nano fillers are Al2O3, TiO2 and clay added in 2.5- 10 wt% by weight ratio. Test samples were prepared using an open mould type die. Mechanical tests were carried out. The tensile strength, elastic modulus, elongation at break and the hardness of the composite materials were obtained and evaluated. It was seen from the results that the filler content had a high influence on the level of the mechanical properties of the epoxy composites.

Keywords: nano, epoxy, composite, fillers, clay

Procedia PDF Downloads 391

Authors: Michael Tupý, Alice Tesaříková-Svobodová, Dagmar Měřínská, Vít Petránek

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Polyethylene (PE), Polypropylene (PP), Polyethylene (vinyl acetate) (EVA) and Surlyn (modif-PE) nano composite samples were prepared with montmorillonite fillers Cloisite 93A and Dellite 67G. The amount of modified Na+ montmorillonite (MMT) was fixed to 5 % (w/w). For the compounding of polymer matrix and chosen nano fillers twin-screw kneader was used. The level of MMT intercalation or exfoliation in the nano composite systems was studied by transmission electron microscopy (TEM) observations. The properties of samples were evaluated by dynamical mechanical analysis (E* modulus at 30 °C) and by the measurement of tensile properties (stress and strain at break).

Keywords: polyethylene, polypropylene, polyethylene(vinyl acetate), clay, nanocomposite, montmorillonite

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Authors: Nileshkumar Vaishnav, Aditya Tatu

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An algebraic framework for processing graph signals axiomatically designates the graph adjacency matrix as the shift operator. In this setup, we often encounter a problem wherein we know the filtered output and the filter coefficients, and need to find out the input graph signal. Solution to this problem using direct approach requires O(N3) operations, where N is the number of vertices in graph. In this paper, we adapt the spectral graph partitioning method for partitioning of graphs and use it to reduce the computational cost of the filtering problem. We use the example of denoising of the temperature data to illustrate the efficacy of the approach.

Keywords: graph signal processing, graph partitioning, inverse filtering on graphs, algebraic signal processing

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Authors: Samra Isadounene, Amar Boukerrou, Dalila Hammiche

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In this work, the composites were prepared with poly(lactic acid) (PLA) and olive husk flour (OHF) with different percentages (10, 20 and 30%) using extrusion method followed by injection molding. The morphological, mechanical properties and thermal behavior of composites were investigated. Tensile strength and elongation at break of composites showed a decreasing trend with increasing fiber content. On the other hand, Young modulus and storage modulus were increased. The addition of OHF resulted in a decrease in thermal stability of composites. The presence of OHF led to an increase in percentage of crystallinity (Xc) of PLA matrix.

Keywords: biopolymers, composites, mechanical properties, poly(lactic acid)

Procedia PDF Downloads 238

Authors: Birute Bugelyte, Ingrida Jurkute, Vida Vickackaite

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The most complicated step of the determination of volatile compounds in complex matrices is the separation of analytes from the matrix. Traditional analyte separation methods (liquid extraction, Soxhlet extraction) require a lot of time and labour; moreover, there is a risk to lose the volatile analytes. In recent years, headspace gas chromatography has been used to determine volatile compounds. To date, traditional extraction solvents have been used in headspace gas chromatography. As a rule, such solvents are rather volatile; therefore, a large amount of solvent vapour enters into the headspace together with the analyte. Because of that, the determination sensitivity of the analyte is reduced, a huge solvent peak in the chromatogram can overlap with the peaks of the analyts. The sensitivity is also limited by the fact that the sample can’t be heated at a higher temperature than the solvent boiling point. In 2018 it was suggested to replace traditional headspace gas chromatographic solvents with non-volatile, eco-friendly, biodegradable, inexpensive, and easy to prepare deep eutectic solvents (DESs). Generally, deep eutectic solvents have low vapour pressure, a relatively wide liquid range, much lower melting point than that of any of their individual components. Those features make DESs very attractive as matrix media for application in headspace gas chromatography. Also, DESs are polar compounds, so they can be applied for microwave assisted extraction. The aim of this work was to investigate the possibility of applying deep eutectic solvents for microwave assisted extraction and headspace gas chromatographic determination of hexanal in fat-rich food. Hexanal is considered one of the most suitable indicators of lipid oxidation degree as it is the main secondary oxidation product of linoleic acid, which is one of the principal fatty acids of many edible oils. Eight hydrophilic and hydrophobic deep eutectic solvents have been synthesized, and the influence of the temperature and microwaves on their headspace gas chromatographic behaviour has been investigated. Using the most suitable DES, microwave assisted extraction conditions and headspace gas chromatographic conditions have been optimized for the determination of hexanal in potato chips. Under optimized conditions, the quality parameters of the prepared technique have been determined. The suggested technique was applied for the determination of hexanal in potato chips and other fat-rich food.

Keywords: deep eutectic solvents, headspace gas chromatography, hexanal, microwave assisted extraction

Procedia PDF Downloads 195

Authors: Kirill M. Dubovikov, Ekaterina S. Marchenko, Gulsharat A. Baigonakova

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NiTi alloys are widely used as implants in medicine due to their unique properties such as superelasticity, shape memory effect and biocompatibility. However, despite these properties, one of the major problems is the release of nickel after prolonged use in the human body under dynamic stress. This occurs due to oxidation and cracking of NiTi implants, which provokes nickel segregation from the matrix to the surface and release into living tissues. As we know, nickel is a toxic element and can cause cancer, allergies, etc. One of the most popular ways to solve this problem is to create a corrosion resistant coating on NiTi. There are many coatings of this type, but not all of them have good biocompatibility, which is very important for medical implants. Coatings based on calcium phosphate phases have excellent biocompatibility because Ca and P are the main constituents of the mineral part of human bone. This fact suggests that a Ca-P coating on NiTi can enhance osteogenesis and accelerate the healing process. Therefore, the aim of this study is to investigate the structure of Ca-P coating on NiTi substrate. Plasma assisted radio frequency (RF) sputtering was used to obtain this film. This method was chosen because it allows the crystallinity and morphology of the Ca-P coating to be controlled by the sputtering parameters. It allows us to obtain three different NiTi samples with Ca-P coating. XRD, AFM, SEM and EDS were used to study the composition, structure and morphology of the coating phase. Scratch tests were carried out to evaluate the adhesion of the coating to the substrate. Wettability tests were used to investigate the hydrophilicity of the different coatings and to suggest which of them had better biocompatibility. XRD showed that the coatings of all samples were hydroxyapatite, but the matrix was represented by TiNi intermetallic compounds such as B2, Ti2Ni and Ni3Ti. The SEM shows that the densest and defect-free coating has only one sample after three hours of sputtering. Wettability tests show that the sample with the densest coating has the lowest contact angle of 40.2° and the largest free surface area of 57.17 mJ/m2, which is mostly disperse. A scratch test was carried out to investigate the adhesion of the coating to the surface and it was shown that all coatings were removed by a cohesive mechanism. However, at a load of 30N, the indenter reached the substrate in two out of three samples, except for the sample with the densest coating. It was concluded that the most promising sputtering mode was the third, which consisted of three hours of deposition. This mode produced a defect-free Ca-P coating with good wettability and adhesion.

Keywords: biocompatibility, calcium phosphate coating, NiTi alloy, radio frequency sputtering.

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Authors: Max Filipe Goncalves, Alessandra Concilio, Rodrigo Shimada

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The waste frying oil is highly pollutant when disposed incorrectly in the environment. Is necessary search of the Reverse Logistics to identify how can be structure to return the waste like this to productive chain and to be used in the new process. In this context, the objective of this paper is to analyze the perspective of the waste frying oil in São Paulo, and its dimensions in the production of biodiesel. Subjacent factors such as the agents, motivators and legal aspects were analyzed to demonstrate it. Then, the SWOT matrix was built with the aspects observed and the forces, weaknesses, opportunities and threats of the reverse logistic chain in São Paulo.

Keywords: biodiesel, perspective, reverse logistic, WFO

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Authors: P. W. Tsai, J. W. Chen, C. W. Chen, C. Y. Chen

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In recent years, many researchers are involved in the field of fuzzy theory. However, there are still a lot of issues to be resolved. Especially on topics related to controller design such as the field of robot, artificial intelligence, and nonlinear systems etc. Besides fuzzy theory, algorithms in swarm intelligence are also a popular field for the researchers. In this paper, a concept of utilizing one of the swarm intelligence method, which is called Bacterial-GA Foraging, to find the stabilized common P matrix for the fuzzy controller system is proposed. An example is given in in the paper, as well.

Keywords: half-circle fuzzy numbers, predictions, swarm intelligence, Lyapunov method

Procedia PDF Downloads 685