Search results for: soil lead contamination.

Authors: B. A. Mir, A. Juneja

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In this paper, shear behavior of reconstituted clay reinforced with varying diameter of sand compaction piles with area replacement-ratio (a_s) of 6.25, 10.24, 16, 20.25 and 64% in 100mm diameter and 200mm long clay specimens is modeled using consolidated drained and undrained triaxial tests under different confining pressures ranging from 50kPa to 575kPa. The test results show that the stress-strain behavior of the clay was highly influenced by the presence of SCP. The insertion of SCPs into soft clay has shown to have a positive effect on the load carrying capacity of the clay, resulting in a composite soil mass that has greater shear strength and improved stiffness compared to the unreinforced clay due to increased reinforcement area ratio. In addition, SCP also acts as vertical drain in the clay thus accelerating the dissipation of excess pore water pressures that are generated during loading by shortening the drainage path and activating radial drainage, thereby reducing post-construction settlement. Thus, sand compaction piles currently stand as one of the most viable and practical techniques for improving the mechanical properties of soft clays.

Keywords: Reconstituted clay, SCP, shear strength, stress-strain response, triaxial tests.

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Authors: D. Sasikala, K. Premalatha

Abstract:

The use of eXtensible Markup Language (XML) in web, business and scientific databases lead to the development of methods, techniques and systems to manage and analyze XML data. Semi-structured documents suffer due to its heterogeneity and dimensionality. XML structure and content mining represent convergence for research in semi-structured data and text mining. As the information available on the internet grows drastically, extracting knowledge from XML documents becomes a harder task. Certainly, documents are often so large that the data set returned as answer to a query may also be very big to convey the required information. To improve the query answering, a Semantic Tree Based Association Rule (STAR) mining method is proposed. This method provides intentional information by considering the structure, content and the semantics of the content. The method is applied on Reuter’s dataset and the results show that the proposed method outperforms well.

Keywords: Semi--structured Document, Tree based Association Rule (TAR), Semantic Association Rule Mining.

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Authors: Norah Alshahrani, Abdulaziz Almaleh

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Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD: Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by SVM, achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: Autism Spectrum Disorder, ASD, Machine Learning, ML, Feature Selection, Support Vector Machine, SVM.

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Authors: H. Barati, M. Wu, A. Kharicha, A. Ludwig

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A transient model for nozzle clogging has been developed and successfully validated against a laboratory experiment. Key steps of clogging are considered: transport of particles by turbulent flow towards the nozzle wall; interactions between fluid flow and nozzle wall, and the adhesion of the particle on the wall; the growth of the clog layer and its interaction with the flow. The current paper is to investigate the mesh (size and type) sensitivity of the model in both two and three dimensions. It is found that the algorithm for clog growth alone excluding the flow effect is insensitive to the mesh type and size, but the calculation including flow becomes sensitive to the mesh quality. The use of 2D meshes leads to overestimation of the clog growth because the 3D nature of flow in the boundary layer cannot be properly solved by 2D calculation. 3D simulation with tetrahedron mesh can also lead to an error estimation of the clog growth. A mesh-independent result can be achieved with hexahedral mesh, or at least with triangular prism (inflation layer) for near-wall regions.

Keywords: Clogging, nozzle, numerical model, simulation.

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Authors: Pirada Techaratpong

Abstract:

This research aims to study value-creation process of producing monk-s bowls, Thai traditional handicrafts, which is facing problems in adapting to the changing society. It also aims to identify problems and obstacles to value creation. This research is based on a case study of monk-s bowl manufactures from Ban-Baat Village, Bangkok. The conceptual framework is based on the model of value chain to analyze the process. The research methodology is qualitative. This research found that the value-creation process of monk-s bowls consists of eight activities contributing to adding value to the products and increasing profits to the producers in return. Five major problems and obstacles are found. The research suggests that these problems and obstacles limit the manufacturers- potential for creating more valued product and lead to business stagnation. These problems should be addressed and solved with collaboration among the government, the private sector and the manufacturers.

Keywords: Craft manufacturing, problems and obstacles, value chain, value creation.

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Authors: M. Azadbakht, M. E. Shayan, H. Jafari, E. Ghajarjazi, A. Kiapei

Abstract:

Transmission shafts are affected by various forces, for example, during acceleration or sudden breaks, bending during transportation, vertical forces that lead to cuts. One of the main failures in combines is breaking shaft which repairmen refer it. Structural resistance of canal against torque is very important in the beginning of the movement. For analyzing stress, a typical sample from a type of combine was selected, called JD955 combine. Long shaft in this combine was analyzed with finite element method by Ansys13 generic package under static load. Conducted analysis showed that there is a maximum stress in contact surfaces of indentations and also in place of changing diameter. Safety factor value is low in parts of the shaft and this increases the probability of failure at these points. To improve the conditions with the least cost and an approach of product improvement, using alternative alloy is important.

Keywords: John Deere, Ansys, Shaft, Stress, Grain Combine harvester, Finite element, Failure.

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Authors: H. Iranmanesh, M. Madadi

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Work Breakdown Structure (WBS) is one of the most vital planning processes of the project management since it is considered to be the fundamental of other processes like scheduling, controlling, assigning responsibilities, etc. In fact WBS or activity list is the heart of a project and omission of a simple task can lead to an irrecoverable result. There are some tools in order to generate a project WBS. One of the most powerful tools is mind mapping which is the basis of this article. Mind map is a method for thinking together and helps a project manager to stimulate the mind of project team members to generate project WBS. Here we try to generate a WBS of a sample project involving with the building construction using the aid of mind map and the artificial intelligence (AI) programming language. Since mind map structure can not represent data in a computerized way, we convert it to a semantic network which can be used by the computer and then extract the final WBS from the semantic network by the prolog programming language. This method will result a comprehensive WBS and decrease the probability of omitting project tasks.

Keywords: Expert System, Mind map, Semantic network, Work breakdown structure,

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Authors: S. M. Al-Salem, G.A. Leeke, H. J. Karam, R. Al-Enzi, A. T. Al-Dhafeeri, J. Wang

Abstract:

Thermogravimetry has been popularized as a thermal characterization technique since the 1950s. It aims at investigating the weight loss against both reaction time and temperature, whilst being able to characterize the evolved gases from the volatile components of the organic material being tested using an appropriate hyphenated analytical technique. In an effort to characterize and identify the reclaimed waste from an unsanitary landfill site, this approach was initiated. Solid waste (SW) reclaimed from an active landfill site in the State of Kuwait was collected and prepared for characterization in accordance with international protocols. The SW was segregated and its major components were identified after washing and air drying. Shredding and cryomilling was conducted on the plastic solid waste (PSW) component to yield a material that is representative for further testing and characterization. The material was subjected to five heating rates (b) with minimal repeatable weight for high accuracy thermogravimetric analysis (TGA) following the recommendation of the International Confederation for Thermal Analysis and Calorimetry (ICTAC). The TGA yielded thermograms that showed an off-set from typical behavior of commercial grade resin which was attributed to contact of material with soil and thermal/photo-degradation.

Keywords: Polymer, TGA, Pollution, Landfill, Waste, Plastic.

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Authors: Iman Iraei, Mina Sharifi

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A method for object tracking in motion blurred images is proposed in this article. This paper shows that object tracking could be improved with this approach. We use mean shift algorithm to track different objects as a main tracker. But, the problem is that mean shift could not track the selected object accurately in blurred scenes. So, for better tracking result, and increasing the accuracy of tracking, wavelet transform is used. We use a feature named as blur extent, which could help us to get better results in tracking. For calculating of this feature, we should use Harr wavelet. We can look at this matter from two different angles which lead to determine whether an image is blurred or not and to what extent an image is blur. In fact, this feature left an impact on the covariance matrix of mean shift algorithm and cause to better performance of tracking. This method has been concentrated mostly on motion blur parameter. transform. The results reveal the ability of our method in order to reach more accurately tracking.

Keywords: Mean shift, object tracking, blur extent, wavelet transform, motion blur.

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Authors: Farzaneh Akhavan Mahdavi, Siti Anom Ahmad, Mohd Hamiruce Marhaban, Mohammad-R. Akbarzadeh-T

Abstract:

Electromyography (EMG) signal processing has been investigated remarkably regarding various applications such as in rehabilitation systems. Specifically, wavelet transform has served as a powerful technique to scrutinize EMG signals since wavelet transform is consistent with the nature of EMG as a non-stationary signal. In this paper, the efficiency of wavelet transform in surface EMG feature extraction is investigated from four levels of wavelet decomposition and a comparative study between different mother wavelets had been done. To recognize the best function and level of wavelet analysis, two evaluation criteria, scatter plot and RES index are recruited. Hereupon, four wavelet families, namely, Daubechies, Coiflets, Symlets and Biorthogonal are studied in wavelet decomposition stage. Consequently, the results show that only features from first and second level of wavelet decomposition yields good performance and some functions of various wavelet families can lead to an improvement in separability class of different hand movements.

Keywords: Electromyography signal, feature extraction, wavelettransform, means absolute value.

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Authors: Bharatendra Rai

Abstract:

Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: Housing data, feature selection, random forest, Boruta algorithm, root mean square error.

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Authors: N. S. Imamverdiyev

Abstract:

The transition to renewable energy sources has become a critical component of global efforts to mitigate climate change and promote sustainable development. However, the deployment of renewable energy technologies can also have significant impacts on ecosystems and the services they provide, such as carbon sequestration, soil fertility, water quality, and biodiversity. These technologies also highlight the potential co-benefits of renewable energy deployment for ecosystem services, such as reducing greenhouse gas emissions and improving air and water quality. Renewable energy sources, such as wind, solar, hydro, and biomass, are increasingly being used to meet the world's energy needs due to their environmentally friendly nature and the desire to reduce greenhouse gas emissions. However, the expansion of renewable energy infrastructure can also impact ecosystem services, which are the benefits that humans derive from nature, such as clean water, air, and food. This geographic assessment aims to evaluate the relationship between renewable energy infrastructure and ecosystem services. Potential solutions such as the use of ecological benefit measures, biodiversity-friendly design of renewable energy infrastructure, and stakeholder participation in decision-making processes are being investigated to determine the positive effects of renewable energy infrastructure on ecosystem services.

Keywords: Renewable energy, solar energy, climate change, energy production.

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Authors: Violina R. Angelova, Mariana N. Perifanova-Nemska, Galina P. Uzunova, Elitsa N. Kolentsova

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Comparative research has been conducted to allow us to determine the accumulation of heavy metals (Pb, Zn and Cd) in the vegetative and reproductive organs of safflower, and to identify the possibility of its growth on soils contaminated by heavy metals and efficacy for phytoremediation. The experiment was performed on an agricultural field contaminated by the Non-Ferrous-Metal Works (MFMW) near Plovdiv, Bulgaria. The experimental plots were situated at different distances (0.1, 0.5, 2.0, and 15 km) from the source of pollution. The contents of heavy metals in plant materials (roots, stems, leaves, seeds) were determined. The quality of safflower oils (heavy metals and fatty acid composition) was also determined. The quantitative measurements were carried out with inductively-coupled plasma (ICP). Safflower is a plant that is tolerant to heavy metals and can be referred to the hyperaccumulators of lead and cadmium and the accumulators of zinc. The plant can be successfully used in the phytoremediation of heavy metal contaminated soils. The processing of safflower seeds into oil and the use of the obtained oil will greatly reduce the cost of phytoremediation.

Keywords: Heavy metals, phytoremediation, polluted soils, safflower.

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Authors: M. Shahar Yar, M. Mustaqeem Abdullah, Jaseela Majeed

Abstract:

A series of 1-(1H-benzimidazol-2-yl)-3-(substituted phenyl)-2-propen-1-one were allowed to react with hydrazine hydrate and phenyl hydrazine in submitted reactions to get pyrazoline and phenyl pyrazoline derivatives. All the compounds entered for screening at the Tuberculosis Antimicrobial Acquisition and Coordinating Facility (TAACF) for their in vitro antibacterial activity against Mycobacterium tuberculosis H37Rv strain (ATCC 27294) using Microplate Alamar Blue Assay (MABA) susceptibility test. The results expressed as MIC (minimum inhibitory concentration) in μg/mL. Among the fifteen compounds, eight compounds were found to have MIC values less than 10 μg/mL. These were subjected for cytotoxicity assay in VERO cells to determine CC50 (cytotoxic concentration 50%) values and finally SI (Selectivity Index) were calculated. Compound (XV) 2-[5-(4- fluorophenyl)-1-phenyl-4,5-dihydro-1H-3-pyrazolyl]-1Hbenzimidazole was considered the best candidate of the series that could be a good starting point to develop new lead compounds in the fight against tuberculosis.

Keywords: anti-tubercular activity, benzimidazole, pyrazoline.

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Authors: Mohammad I. Hossain, Omar F. Hamim

Abstract:

This paper presents a case study on a pile integrity test for assessing the integrity of piles as well as a physical dimension (e.g., cross-sectional area, length), continuity, and consistency of the pile materials. The recent boom in the socio-economic condition of Bangladesh has given rise to the building of high-rise commercial and residential infrastructures. The advantage of the pile integrity test lies in the fact that it is possible to get an approximate indication regarding the quality of the sub-structure before commencing the construction of the super-structure. This paper aims at providing a classification of cast-in-situ piles based on characteristic reflectograms obtained using the Sonic Integrity Testing program for the sub-soil condition of Narayanganj, Bangladesh. The piles have been classified as 'Pile Type-1', 'Pile Type-2', 'Pile Type-3', 'Pile type-4', 'Pile Type-5' or 'Pile Type-6' from the visual observations of reflections from the generated stress waves by striking the pile head with a handheld hammer. With respect to construction quality and integrity, piles have been further classified into three distinct categories, i.e., satisfactory, may be satisfactory, and unsatisfactory.

Keywords: Cast-in-situ piles, characteristic reflectograms, pile integrity test, sonic integrity testing program.

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Authors: Carolina B. Baguio

Abstract:

One of the purposes of the robust method of estimation is to reduce the influence of outliers in the data, on the estimates. The outliers arise from gross errors or contamination from distributions with long tails. The trimmed mean is a robust estimate. This means that it is not sensitive to violation of distributional assumptions of the data. It is called an adaptive estimate when the trimming proportion is determined from the data rather than being fixed a “priori-. The main objective of this study is to find out the robustness properties of the adaptive trimmed means in terms of efficiency, high breakdown point and influence function. Specifically, it seeks to find out the magnitude of the trimming proportion of the adaptive trimmed mean which will yield efficient and robust estimates of the parameter for data which follow a modified Weibull distribution with parameter λ = 1/2 , where the trimming proportion is determined by a ratio of two trimmed means defined as the tail length. Secondly, the asymptotic properties of the tail length and the trimmed means are also investigated. Finally, a comparison is made on the efficiency of the adaptive trimmed means in terms of the standard deviation for the trimming proportions and when these were fixed a “priori". The asymptotic tail lengths defined as the ratio of two trimmed means and the asymptotic variances were computed by using the formulas derived. While the values of the standard deviations for the derived tail lengths for data of size 40 simulated from a Weibull distribution were computed for 100 iterations using a computer program written in Pascal language. The findings of the study revealed that the tail lengths of the Weibull distribution increase in magnitudes as the trimming proportions increase, the measure of the tail length and the adaptive trimmed mean are asymptotically independent as the number of observations n becomes very large or approaching infinity, the tail length is asymptotically distributed as the ratio of two independent normal random variables, and the asymptotic variances decrease as the trimming proportions increase. The simulation study revealed empirically that the standard error of the adaptive trimmed mean using the ratio of tail lengths is relatively smaller for different values of trimming proportions than its counterpart when the trimming proportions were fixed a 'priori'.

Keywords: Adaptive robust estimate, asymptotic efficiency, breakdown point, influence function, L-estimates, location parameter, tail length, Weibull distribution.

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Authors: Mansur Hamma-adama, Abdul-Basit Sa’eed Ahmad

Abstract:

Construction Industry is evolving amid the fourth industrial revolution. Transportation, commerce, manufacturing and many other industries ripened the current technological advancement and are striving to utilise every development in the IT sector. The procurement of construction works is known to be very conventional and backward in the adoption of digitalisation. The construction industry's procurement and supply chain are blamed for the most inflated cost of construction projects, mainly attributed to a lack of transparency and trust between the industry stakeholders. This research explores the challenges of e-procurement adoption in the industry and identifies the potential opportunities for its usage. This investigation's data are acquired through interviews, and the data are analysed using qualitative content analysis. This study reveals compounding challenges (i.e., corruption and lack of commitment) that lead to the failure of such efforts in Nigeria and the potential prospects (i.e., transparency and efficiency). This study is essential in developing a more effective and transparent process of procurement so that the Nigerian construction industry is not be left behind in the fast-digitalising markets.

Keywords: Challenges, construction industry, corruption, e-procurement, Nigeria, opportunities.

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Authors: Dabiri Y, Najarian S, Eslami M R., Zahedi S, Moser D, Shirzad E, Allami M

Abstract:

The effect of muscle loss due to transfemoral amputation, on energy expenditure of hip joint and individual residual muscles was simulated. During swing phase of gait, with each muscle as an ideal force generator, the lower extremity was modeled as a two-degree of freedom linkage, for which hip and knee were joints. According to results, muscle loss will not lead to higher energy expenditure of hip joint, as long as other parameters of limb remain unaffected. This finding maybe due to the role of biarticular muscles in hip and knee joints motion. Moreover, if hip flexors are removed from the residual limb, residual flexors, and if hip extensors are removed, residual extensors will do more work. In line with the common practice in transfemoral amputation, this result demonstrates during transfemoral amputation, it is important to maintain the length of residual limb as much as possible.

Keywords: Amputation Level, Simulation, Transfemoral Amputee.

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Authors: R.M.Rani

Abstract:

Chess is one of the indoor games, which improves the level of human confidence, concentration, planning skills and knowledge. The main objective of this paper is to help the chess players to improve their chess openings using data mining techniques. Budding Chess Players usually do practices by analyzing various existing openings. When they analyze and correlate thousands of openings it becomes tedious and complex for them. The work done in this paper is to analyze the best lines of Blackmar- Diemer Gambit(BDG) which opens with White D4... using data mining analysis. It is carried out on the collection of winning games by applying association rules. The first step of this analysis is assigning variables to each different sequence moves. In the second step, the sequence association rules were generated to calculate support and confidence factor which help us to find the best subsequence chess moves that may lead to winning position.

Keywords: Blackmar-Diemer Gambit(BDG), Confidence, sequence Association Rules, Support.

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Authors: Mohd Abdullah

Abstract:

This review describes some of the effects of repetitive strain/stress injury (RSI) on the human body especially among computer professionals today that spend extended hours of prolonged sitting in front of a computer day in and day out. The review briefly introduces the main factors that contribute to an increase of RSI among such computer professionals. The review briefly discusses how the human spinal column and knees are mainly affected by the onset of RSI resulting in poor posture. The root and secondary causes and effects of RSI are reviewed. The importance and value of the various breathing techniques are reviewed in an attempt to alleviate some of the effects of RSI. The review concludes with a small sample of suggested office stretches and poses geared towards at reducing RSI follows in this review. Readers will learn about the effects of RSI, as well as ways to cope with it. A better understanding of coping strategies may lead to well-being and a healthier overall lifestyle. Ultimately, the investment of time to connect with oneself with the poses and the power of the breath would promote a well-being that is overall healthier thus resulting in a better ability to cope/manage life stresses.

Keywords: Health, wellness, repetitive, chairs.

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Authors: Hatem A. Khater, A. Baith Mohamed, Sara M. Kamel

Abstract:

Software Development Risks Identification (SDRI), using Fault Tree Analysis (FTA), is a proposed technique to identify not only the risk factors but also the causes of the appearance of the risk factors in software development life cycle. The method is based on analyzing the probable causes of software development failures before they become problems and adversely affect a project. It uses Fault tree analysis (FTA) to determine the probability of a particular system level failures that are defined by A Taxonomy for Sources of Software Development Risk to deduce failure analysis in which an undesired state of a system by using Boolean logic to combine a series of lower-level events. The major purpose of this paper is to use the probabilistic calculations of Fault Tree Analysis approach to determine all possible causes that lead to software development risk occurrence

Keywords: Software Development Risks Identification (SDRI), Fault Tree Analysis (FTA), Taxonomy for Software Development Risks (TSDR), Probabilistic Risk Assessment (PRA).

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Authors: Usha Sridhar, Sridhar Mandyam

Abstract:

We propose a multi-agent based utilitarian approach to model and understand information flows in social networks that lead to Pareto optimal informational exchanges. We model the individual expected utility function of the agents to reflect the net value of information received. We show how this model, adapted from a theorem by Karl Borch dealing with an actuarial Risk Exchange concept in the Insurance industry, can be used for social network analysis. We develop a utilitarian framework that allows us to interpret Pareto optimal exchanges of value as potential information flows, while achieving a maximization of a sum of expected utilities of information of the group of agents. We examine some interesting conditions on the utility function under which the flows are optimal. We illustrate the promise of this new approach to attach economic value to information in networks with a synthetic example.

Keywords: Borch's Theorem , Economic value of information, Information Exchange, Pareto Optimal Solution, Social Networks, Utility Functions

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Authors: N. Gigauri, A. Surmava

Abstract:

According to observational data, experimental measurements and numerical modelling, the pollution of one of the industrial centers of Georgia, Rustavi City’s atmosphere with micro aerosols are assessed. Monthly, daily and hourly changes of the concentrations of PM2.5 and PM10 in the city atmosphere are analyzed. It is accepted that PM2.5 concentrations are always lower than PM10 concentrations, but their change curve is the same. In addition, it has been noted that the maximum concentrations of particles in the atmosphere of Rustavi city will be reached at any part of the day, which is determined by the total impact of the traffic flow and industrial facilities. Through numerical modelling, the influence of background western light air, gentle and fresh breeze on the distribution of particulate matter in the atmosphere was calculated. Calculations showed that background light air and gentle breeze lead to an increase the concentrations of microaerosols in the city's atmosphere, while fresh breeze contributes to the dispersion of dusty clouds. As a result, the level of dust in the city is decreasing, but the distribution area is expanding.

Keywords: Air pollution, numerical modeling, experimental measurement, PM2.5, PM10.

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Authors: Sandya Mummullage, Prasanna Egodawatta, Ashantha Goonetilleke, Godwin A. Ayoko

Abstract:

Urban road dust comprises of a range of potentially  toxic metal elements and plays a critical role in degrading urban  receiving water quality. Hence, assessing the metal composition and  concentration in urban road dust is a high priority. This study  investigated the variability of metal composition and concentrations  in road dust in 4 different urban land uses in Gold Coast, Australia.  Samples from 16 road sites were collected and tested for selected 12  metal species. The data set was analyzed using both univariate and  multivariate techniques. Outcomes of the data analysis revealed that  the metal concentrations inroad dust differs considerably within and  between different land uses. Iron, aluminum, magnesium and zinc are  the most abundant in urban land uses. It was also noted that metal  species such as titanium, nickel, copper and zinc have the highest  concentrations in industrial land use. The study outcomes revealed  that soil and traffic related sources as key sources of metals deposited  on road surfaces.

 

Keywords: Metals build-up, Pollutant accumulation, Stormwater quality, Urban road dust.

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Authors: Fanqiang Kong, Chending Bian

Abstract:

In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l_2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: Hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation.

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Authors: Yong Ren, Yaping Zhang

Abstract:

A numerical model has been developed to investigate the thermally triggered release kinetics for drug delivery using phase change material as shell of microcapsules. Biocompatible material n-Eicosane is used as demonstration. PCM shell of microcapsule will remain in solid form after the drug is taken, so the drug will be encapsulated by the shell, and will not be released until the target body part of lesion is exposed to external heat source, which will thermally trigger the release kinetics, leading to solid-to-liquid phase change. The findings can lead to better understanding on the key effects influencing the phase change process for drug delivery applications. The facile approach to release drug from core/shell structure of microcapsule can be well integrated with organic solvent free fabrication of microcapsules, using double emulsion as template in microfluidic aqueous two phase system.

Keywords: Phase change material, drug release kinetics, double emulsion, microfluidics.

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Authors: Pengfei Xiong, Lei Huang, Changping Liu

Abstract:

In illumination variant face recognition, existing methods extracting face albedo as light normalized image may lead to loss of extensive facial details, with light template discarded. To improve that, a novel approach for realistic facial texture reconstruction by combining original image and albedo image is proposed. First, light subspaces of different identities are established from the given reference face images; then by projecting the original and albedo image into each light subspace respectively, texture reference images with corresponding lighting are reconstructed and two texture subspaces are formed. According to the projections in texture subspaces, facial texture with normal light can be synthesized. Due to the combination of original image, facial details can be preserved with face albedo. In addition, image partition is applied to improve the synthesization performance. Experiments on Yale B and CMUPIE databases demonstrate that this algorithm outperforms the others both in image representation and in face recognition.

Keywords: texture reconstruction, illumination, face recognition, subspaces

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Authors: Ratchada Sopakayang, Gerhard A. Holzapfel

Abstract:

In this study, a new constitutive model is developed to describe the hyperelastic behavior of collagenous tissues with a parallel arrangement of collagen fibers such as ligaments and tendons. The model is formulated using a continuum approach incorporating the structural changes of the main tissue components: collagen fibers, proteoglycan-rich matrix and fiber-matrix interaction. The mechanical contribution of the interaction between the fibers and the matrix is simply expressed by a coupling term. The structural change of the collagen fibers is incorporated in the constitutive model to describe the activation of the fibers under tissue straining. Finally, the constitutive model can easily describe the stress-stretch nonlinearity which occurs when a ligament/tendon is axially stretched. This study shows that the interaction between the fibers and the matrix contributes to the mechanical tissue response. Therefore, the model may lead to a better understanding of the physiological mechanisms of ligaments and tendons under axial loading.

Keywords: Hyperelasticity, constitutive model, fiber-matrix interaction, ligament, tendon.

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Authors: I. Gokasar, G. Bakioglu

Abstract:

With the unprecedented rates of technological improvements, people start to solve their problems with the help of technological tools. According to application stores and websites in which people evaluate and comment on the traffic apps, there are more than 100 traffic applications which have different features with respect to their purpose of usage ranging from the features of traffic apps for public transit modes to the features of traffic apps for private cars. This study focuses on the top 30 traffic applications which were chosen with respect to their download counts. All data about the traffic applications were obtained from related websites. The purpose of this study is to analyze traffic applications in terms of their categorical attributes with the help of developing a regression model. The analysis results suggest that negative interpretations (e.g., being deficient) does not lead to lower star ratings of the applications. However, those negative interpretations result in a smaller increase in star rate. In addition, women use higher star rates than men for the evaluation of traffic applications.

Keywords: Traffic App, real–time information, traffic congestion, regression analysis, dummy variables.

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Authors: Govind Shay Sharma, Randhir Singh Baghel

Abstract:

The stock management of raw materials and finished goods is a significant issue for industries in fulfilling customer demand. Optimization of inventory strategies is crucial to enhancing customer service, reducing lead times and costs, and meeting market demand. This paper suggests finding an approach to predict the optimum stock level by utilizing past stocks and forecasting the required quantities. In this paper, we utilized Artificial Neural Network (ANN) to determine the optimal value. The objective of this paper is to discuss the optimized ANN that can find the best solution for the inventory model. In the context of the paper, we mentioned that the k-means algorithm is employed to create homogeneous groups of items. These groups likely exhibit similar characteristics or attributes that make them suitable for being managed using uniform inventory control policies. The paper proposes a method that uses the neural fit algorithm to control the cost of inventory.

Keywords: Artificial Neural Network, inventory management, optimization, distributor center.

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