Search results for: particle union optimization algorithm

Authors: Hoi-Lam Ma, Sai-Ho Chung

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In traditional integrated berth allocation with quay crane assignment models, time dimension is usually assumed in hourly based. However, nowadays, transshipment becomes the main business to many container terminals, especially in Southeast Asia (e.g. Hong Kong and Singapore). In these terminals, vessel arrivals are usually very frequent with small handling volume and very short staying time. Therefore, the traditional hourly-based modeling approach may cause significant berth and quay crane idling, and consequently cannot meet their practical needs. In this connection, a 15-minute-based modeling approach is requested by industrial practitioners. Accordingly, a Three-level Genetic Algorithm (3LGA) with Quay Crane (QC) shifting heuristics is designed to fulfill the research gap. The objective function here is to minimize the total service time. Preliminary numerical results show that the proposed 15-minute-based approach can reduce the berth and QC idling significantly.

Keywords: transshipment, integrated berth allocation, variable-in-time quay crane assignment, quay crane assignment

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Authors: Mohammad A. M. Kewisha

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Xerophilic fungi , which are responsible for many cases of biodeterioration monuments, have been known as an interesting source of antimicrobial compounds. Sixty nine fungal strains, isolated from different localities and species inside Egyptian museums, were screened for antimicrobial activity against some bacterial species and unicellular fungi. The most potent antimicrobial activity was obtained by Asperigillus fumigatus which was identified by ITS4 ……. and showed activity against Staphylococcus aureus with 20 mm and C. albicans with18 mm of inhibition zone. Different parameters were optimized to enhance this activity. The culture grown under stationary conditions for 8 days at 30°C and pH 8 gave the best antimicrobial activity. Moreover, both starch and yeast extract showed the most suitable carbon and nitrogen sources, respectively. The antimicrobial compound was purified and subjected to spectroscopic characterization, which revealed that the antimicrobial compound might be 5,7 ethoxy, 4\,5\ methoxy isorhamnetin -3- O- galactoside. This study suggests that Aspergillus fumagates as a potential candidate offering a better scope for the production, purification and isolation of broad-spectrum antimicrobial compounds. These findings will facilitate the scale-up and further purification to ascertain the compounds responsible for antimicrobial activity, which can be exploited for the treatment of biodeterioration monuments and pharmaceutical applications.

Keywords: antimicrobial activity, asperigillus fumigatus, Identification by ITS4, Staphylococcus aureus, C.albicans

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Authors: George Kurian, Hongmei Chi

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Digital evidence plays a critical role in most legal investigations. In many cases, thumbnail databases show important information in that investigation. The probability of having digital evidence retrieved from a computer or smart device has increased, even though the previous user removed data and deleted apps on those devices. Due to the increase in digital forensics, the ability to store residual information from various thumbnail applications has improved. This paper will focus on investigating thumbnail information from Windows 10. Thumbnail images of interest in forensic investigations may be intact even when the original pictures have been deleted. It is our research goal to recover useful information from thumbnails. In this research project, we use various forensics tools to collect left thumbnail information from deleted videos or pictures. We examine and describe the various thumbnail sources in Windows and propose a methodology for thumbnail collection and analysis from laptops or desktops. A machine learning algorithm is adopted to help speed up content from thumbnail pictures.

Keywords: digital forensic, forensic tools, soundness, thumbnail, machine learning, OCR

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Authors: Zikiou Nadia, Lahdir Mourad, Ameur Soltane

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In this paper, we propose an effective method for image compression based on SVM Regression (SVR), with three different kernels, and biorthogonal 2D Discrete Wavelet Transform. SVM regression could learn dependency from training data and compressed using fewer training points (support vectors) to represent the original data and eliminate the redundancy. Biorthogonal wavelet has been used to transform the image and the coefficients acquired are then trained with different kernels SVM (Gaussian, Polynomial, and Linear). Run-length and Arithmetic coders are used to encode the support vectors and its corresponding weights, obtained from the SVM regression. The peak signal noise ratio (PSNR) and their compression ratios of several test images, compressed with our algorithm, with different kernels are presented. Compared with other kernels, Gaussian kernel achieves better image quality. Experimental results show that the compression performance of our method gains much improvement.

Keywords: image compression, 2D discrete wavelet transform (DWT-2D), support vector regression (SVR), SVM Kernels, run-length, arithmetic coding

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Authors: Z. Kourdi, B. Bouazza, M. Khaouani, A. Guen-Bouazza, Z. Djennati, A. Boursali

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We present a simulation of a HEMT (high electron mobility transistor) structure with and without a field plate. We extract the device characteristics through the analysis of DC, AC and high frequency regimes, as shown in this paper. This work demonstrates the optimal device with a gate length of 15 nm, InAlN/GaN heterostructure and field plate structure, making it superior to modern HEMTs when compared with otherwise equivalent devices. This improves the ability to bear the burden of the current density passes in the channel. We have demonstrated an excellent current density, as high as 2.05 A/mm, a peak extrinsic transconductance of 590 mS/mm at VDS=2 V, and cutting frequency cutoffs of 638 GHz in the first HEMT and 463 GHz for Field plate HEMT., maximum frequency of 1.7 THz, maximum efficiency of 73%, maximum breakdown voltage of 400 V, DIBL=33.52 mV/V and an ON/OFF current density ratio higher than 1 x 1010. These values were determined through the simulation by deriving genetic and Monte Carlo algorithms that optimize the design and the future of this technology.

Keywords: HEMT, Silvaco, field plate, genetic algorithm, quantum

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Authors: Pardeep Singh, Kamlesh Dutta

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Many languages have fixed sentence structure and others are free word order. The accuracy of anaphora resolution of syntax based algorithm depends on structure of the sentence. So, it is important to analyze the structure of any language before implementing these algorithms. In this study, we analyzed the sentence structure exploiting the case marker in Hindi as well as some special tag for subject and object. We also investigated the word order for Hindi. Word order typology refers to the study of the order of the syntactic constituents of a language. We analyzed 165 news items of Ranchi Express from EMILEE corpus of plain text. It consisted of 1745 sentences. Eight file of dialogue based from the same corpus has been analyzed which will have 1521 sentences. The percentages of subject object verb structure (SOV) and object subject verb (OSV) are 66.90 and 33.10, respectively.

Keywords: anaphora resolution, free word order languages, SOV, OSV

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Authors: Muhammad Shahzad Shifa, Amna Shifa, Muhammad Omar, Aamir Shahzad, Rahmat Ali Khan

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Many applications of remote sensing to vegetation and crop response depend on spectral properties of individual leaves and plants. Vegetation indices are usually determined to estimate crop biophysical parameters like crop canopies and crop leaf area indices with the help of remote sensing. Cotton crops assessment is performed with the help of vegetative indices. Remotely sensed images from an optical multispectral radiometer MSR5 are used in this study. The interpretation is based on the fact that different materials reflect and absorb light differently at different wavelengths. Non-normalized and normalized forms of these datasets are analyzed using two complementary data mining algorithms; K-means and K-nearest neighbor (KNN). Our analysis shows that the use of normalized reflectance data and vegetative indices are suitable for an automated assessment and decision making.

Keywords: cotton, condition assessment, KNN algorithm, clustering, MSR5, vegetation indices

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Authors: Ebrahim Safarian, Kadir Bilen, Akif Ceviz

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The turbocharger and turbocharging have been the inherent component of diesel engines, so that critical parameters of such engines, as BSFC(Brake Specific Fuel Consumption) or thermal efficiency, fuel consumption, BMEP(Brake Mean Effective Pressure), the power density output and emission level have been improved extensively. In general, the turbocharger can be considered as the most complex component of diesel engines, because it has closely interrelated turbomachinery concepts of the turbines and the compressors to thermodynamic fundamentals of internal combustion engines and stress analysis of all components. In this paper, a waste gate for a conventional single stage radial turbine is investigated by consideration of turbochargers operation constrains and engine operation conditions, without any detail designs in the turbine and the compressor. Amount of opening waste gate which extended between the ranges of full opened and closed valve, is demonstrated by limiting compressor boost pressure ratio. Obtaining of an optimum point by regard above mentioned items is surveyed by three linked meanline modeling programs together which consist of Turbomatch®, Compal®, Rital®madules in concepts NREC® respectively.

Keywords: turbocharger, wastegate, diesel engine, concept NREC programs

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Authors: Yong-Heng Shi, Peng Hao, Bai-Chen Xie

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Solar prosumers are playing increasingly prominent roles in the power system. However, its uncertainty affects the outcomes and functions of the power market, especially in the asymmetric information environment. Therefore, an important issue is how to take effective measures to reduce the impact of uncertainty on market equilibrium. We propose a two-level stochastic differential game model to explore the Cournot decision problem of prosumers. In particular, we study the impact of punishment and cooperation mechanisms on the efficiency of the Cournot game in which prosumers face uncertainty. The results show that under the penalty mechanism of fixed and variable rates, producers and consumers tend to take conservative actions to hedge risks, and the variable rates mechanism is more reasonable. Compared with non-cooperative situations, prosumers can improve the efficiency of the game through cooperation, which we attribute to the superposition of market power and uncertainty reduction. In addition, the market environment of asymmetric information intensifies the role of uncertainty. It reduces social welfare but increases the income of prosumers. For regulators, promoting alliances is an effective measure to realize the integration, optimization, and stable grid connection of producers and consumers.

Keywords: Cournot games, power market, uncertainty, prosumer cooperation

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Authors: Albert W. K. Tan

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This research consolidates a comprehensive array of publications from peer-reviewed journals, case studies, and seminar reports focused on reverse logistics and network design. By synthesizing this secondary knowledge, our objective is to identify and articulate key decision factors crucial to reverse logistics network design for e-commerce. Through this exploration, we aim to present a refined mathematical model that offers valuable insights for companies seeking to optimize their reverse logistics operations. The primary goal of this research endeavor is to develop a comprehensive framework tailored to advising organizations and companies on crafting effective networks for their reverse logistics operations, thereby facilitating the achievement of their organizational goals. This involves a thorough examination of various network configurations, weighing their advantages and disadvantages to ensure alignment with specific business objectives. The key objectives of this research include: (i) Identifying pivotal factors pertinent to network design decisions within the realm of reverse logistics across diverse supply chains. (ii) Formulating a structured framework designed to offer informed recommendations for sound network design decisions applicable to relevant industries and scenarios. (iii) Propose a mathematical model to optimize its reverse logistics network. A conceptual framework for designing a reverse logistics network has been developed through a combination of insights from the literature review and information gathered from company websites. This framework encompasses four key stages in the selection of reverse logistics operations modes: (1) Collection, (2) Sorting and testing, (3) Processing, and (4) Storage. Key factors to consider in reverse logistics network design: I) Centralized vs. decentralized processing: Centralized processing, a long-standing practice in reverse logistics, has recently gained greater attention from manufacturing companies. In this system, all products within the reverse logistics pipeline are brought to a central facility for sorting, processing, and subsequent shipment to their next destinations. Centralization offers the advantage of efficiently managing the reverse logistics flow, potentially leading to increased revenues from returned items. Moreover, it aids in determining the most appropriate reverse channel for handling returns. On the contrary, a decentralized system is more suitable when products are returned directly from consumers to retailers. In this scenario, individual sales outlets serve as gatekeepers for processing returns. Considerations encompass the product lifecycle, product value and cost, return volume, and the geographic distribution of returns. II) In-house vs. third-party logistics providers: The decision between insourcing and outsourcing in reverse logistics network design is pivotal. In insourcing, a company handles the entire reverse logistics process, including material reuse. In contrast, outsourcing involves third-party providers taking on various aspects of reverse logistics. Companies may choose outsourcing due to resource constraints or lack of expertise, with the extent of outsourcing varying based on factors such as personnel skills and cost considerations. Based on the conceptual framework, the authors have constructed a mathematical model that optimizes reverse logistics network design decisions. The model will consider key factors identified in the framework, such as transportation costs, facility capacities, and lead times. The authors have employed mixed LP to find the optimal solutions that minimize costs while meeting organizational objectives.

Keywords: reverse logistics, supply chain management, optimization, e-commerce

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Authors: Vibha Venkataramu, B. V. Venkatarama Reddy

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Natural river sand is the most preferred choice as fine aggregate in masonry mortars. Uncontrolled mining of sand from riverbeds for several decades has had detrimental effects on the environment. Several countries across the world have put strict restrictions on sand mining from riverbeds. However, in countries like India, the huge infrastructural boom has made the local construction industry to look for alternative materials to sand. This study aims at understanding the suitability of granulated blast furnace slag (GBS) as fine aggregates in masonry mortars. Apart from characterising the material properties of GBS, such as particle size distribution, pH, chemical composition, etc., of GBS, tests were performed on the mortars with GBS as fine aggregate. Additionally, the properties of five brick tall, stack bonded masonry prisms with various types of GBS mortars were studied. The mortars with mix proportions 1: 0: 6 (cement: lime: fine aggregate), 1: 1: 6, and 1: 0: 3 were considered for the study. Fresh and hardened properties of mortar, such as flow and compressive strength, were studied. To understand the behaviour of GBS mortars on masonry, tests such as compressive strength and flexure bond strength were performed on masonry prisms made with a different type of GBS mortars. Furthermore, the elastic properties of masonry with GBS mortars were also studied under compression. For comparison purposes, the properties of corresponding control mortars with natural sand as fine aggregate and masonry prisms with sand mortars were also studied under similar testing conditions. From the study, it was observed the addition of GBS negatively influenced the flow of mortars and positively influenced the compressive strength. The GBS mortars showed 20 to 25 % higher compressive strength at 28 days of age, compared to corresponding control mortars. Furthermore, masonry made with GBS mortars showed nearly 10 % higher compressive strengths compared to control specimens. But, the impact of GBS on the flexural strength of masonry was marginal.

Keywords: building materials, fine aggregate, granulated blast furnace slag in mortars, masonry properties

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Authors: Kai-Chee Loh, Jingxin Zhang, Yen-Wah Tong

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Hydrolysis and acidogenesis are the rate-controlling steps in an anaerobic digestion (AD) process. Considering that the optimum conditions for each stage can be diverse diverse, the development of a multi-stage AD system is likely to the AD efficiency through individual optimization. In this research, we developed a highly integrate three-stage anaerobic digester (HM3) to combine the advantages of dry AD and wet AD for anaerobic co-digestion of food waste and horse manure. The digester design comprised mainly of three chambers - high-solids hydrolysis, high-solids acidogenesis and wet methanogensis. Through comparing the treatment performance with other two control digesters, HM3 presented 11.2 ~22.7% higher methane yield. The improved methane yield was mainly attributed to the functionalized partitioning in the integrated digester, which significantly accelerated the solubilization of solid organic matters and the formation of organic acids, as well as ammonia in the high-solids hydrolytic and acidogenic stage respectively. Additionally, HM3 also showed the highest volatile solids reduction rate among the three digesters. Real-time PCR and pyrosequencing analysis indicated that the abundance and biodiversity of microorganisms including bacteria and archaea in HM3 was much higher than that in the control reactors.

Keywords: anaerobic digestion, high-solids, food waste and horse manure, microbial community

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Authors: M. H. Fazel Zarandi, N. Moshahedi

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The hub location problem appears in a variety of applications such as medical centers, firefighting facilities, cargo delivery systems and telecommunication network design. The location of service centers has a strong influence on the congestion at each of them, and, consequently, on the quality of service. This paper presents a fuzzy maximal hub covering location problem (FMCHLP) in which travel costs between any pair of nodes is considered as a fuzzy variable. In order to consider the quality of service, we model each hub as a queue. Arrival rate follows Poisson distribution and service rate follows Erlang distribution. In this paper, at first, a nonlinear mathematical programming model is presented. Then, we convert it to the linear one. We solved the linear model using GAMS software up to 25 nodes and for large sizes due to the complexity of hub covering location problems, and simulated annealing algorithm is developed to solve and test the model. Also, we used possibilistic c-means clustering method in order to find an initial solution.

Keywords: fuzzy modeling, location, possibilistic clustering, queuing

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Authors: Muhammad Rizwan Tabassum, Ao Xia, Jerry D. Murphy

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The purpose of this work is to provide a comprehensive overview of seaweed as the alternative feedstock for biofuel production and key conversion technologies. Resource depletion and climate change are the driving forces to hunt for renewable sources of energy. Macroalgae can be preferred over land based crops for biofuel production because they are not in competition with food crops for arable land, high growth rates and low lignin contents which require less energy-intensive pre-treatments. However, some disadvantages, such as high moisture content, seasonal variation in chemical composition and process inhibition limit its economic feasibility. Seaweed can be converted into gaseous and liquid fuel by different conversion technologies, but biogas via anaerobic digestion from seaweed is attracting increased attention due to its dual benefit of an economic source of bio-fuel and environment-friendly technology. Biodiesel and bioethanol conversion technologies from seaweed are still under development. A selection of high yielding seaweed species, optimal harvesting season and process optimization make them economically feasible for the alternative source of renewable and sustainable feedstock for biofuel in future.

Keywords: anaerobic digestion, biofuel, bio-methane, conversion technologies, seaweed

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Authors: Chunying Fang, Haifeng Li, Lin Ma, Mancai Zhang

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Speech intelligibility assessment is an important measure to evaluate the functional outcomes of surgical and non-surgical treatment, speech therapy and rehabilitation. The assessment of pathological speech plays an important role in assisting the experts. Pathological speech usually is non-stationary and mutational, in this paper, we describe a multi-granularity combined feature schemes, and which is optimized by hierarchical visual method. First of all, the difference granularity level pathological features are extracted which are BAFS (Basic acoustics feature set), local spectral characteristics MSCC (Mel s-transform cepstrum coefficients) and nonlinear dynamic characteristics based on chaotic analysis. Latterly, radar chart and F-score are proposed to optimize the features by the hierarchical visual fusion. The feature set could be optimized from 526 to 96-dimensions.The experimental results denote that new features by support vector machine (SVM) has the best performance, with a recognition rate of 84.4% on NKI-CCRT corpus. The proposed method is thus approved to be effective and reliable for pathological speech intelligibility evaluation.

Keywords: pathological speech, multi-granularity feature, MSCC (Mel s-transform cepstrum coefficients), F-score, radar chart

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Authors: Mohammed A. M. Ibrahim

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This paper investigate the utilization of wire and wireless networks to be platform for distributed educational monitoring system. Universities in developing countries suffer from a lot of shortages(staff, equipment, and finical budget) and optimal utilization of the wire and wireless network, so universities can mitigate some of the mentioned problems and avoid the problems that maybe humble the education processes in many universities by using our implementation of the examinations system as a test-bed to utilize the network as a solution to the shortages for academic staff in Taiz University. This paper selects a two areas first one quizzes activities is only a test bed application for wireless network learning environment system to be distributed among students. Second area is the features and the security of wireless, our tested application implemented in a promising area which is the use of WLAN in higher education for leering environment.

Keywords: networking wire and wireless technology, wireless network security, distributed computing, algorithm, encryption and decryption

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Authors: Ghulam Mustafa Peerzada, Shagufta Rashid, Nadeem Bashir

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These the influence of initial reagent concentrations on the Belousov-Zhabotinsky (BZ) system with Mn2+/Mn3+ as redox catalyst, inorganic bromate as oxidant and pyrogallol as organic substrate was studied. The reactions were monitored by potentiometery in oxidation reduction potential (ORP) mode. The aforesaid reagents were mixed with varying concentrations to evolve the optimal concentrations at which the reaction system exhibited better oscillations. The various oscillatory parameters such as induction period (tin), time period (tp), frequency (v), amplitude (A) and number of oscillations (n) were derived and the dependence of concentration of the reacting species on these oscillatory parameters was interpreted on the basis of the Field-Koros-Noyes mechanism. Ferroin based BZ system with pyrogallol as organic substrate was optimized under CSTR condition at temperature of 30±0.1oC Effect of molecules like monomer and polymer as additives to the system was checked and their interaction with the system was also studied. It has been observed that the monomer affects the time period, while the polymer has its effect on the amplitude of oscillations because of monomer’s interaction with the bromine and polymer’s with that of the Ferroin.

Keywords: Belousov Zhabotinsky reaction, oscillatory parameters, polymer, pyrogallol

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Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

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This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: landslide, limit analysis, artificial neural network, soil properties

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Authors: Meziani Samir, Moussi Abderrahmane, Chaouchi Sofiane, Guendouzi Awatif, Djema Oussama

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Laser doping has a large potential for integration into silicon solar cell technologies. The ability to process local, heavily diffused regions in a self-aligned manner can greatly simplify processing sequences for the fabrication of selective emitter. The choice of laser parameters for a laser doping process with 532nm is investigated. Solid state lasers with different power and speed were used for laser doping. In this work, the aim is the formation of selective emitter solar cells with a reduced number of technological steps. In order to have a highly doped localized emitter region, we used a 532 nm laser doping. Note that this region will receive the metallization of the Ag grid by screen printing. For this, we use SOLIDWORKS software to design a single type of pattern for square silicon cells. Sheet resistances, phosphorus doping concentration and silicon bulk lifetimes of irradiated samples are presented. Additionally, secondary ion mass spectroscopy (SIMS) profiles of the laser processed samples were acquired. Scanning electron microscope and optical microscope images of laser processed surfaces at different parameters are shown and compared.

Keywords: laser doping, selective emitter, silicon, solar cells

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Authors: J. K. Alhassan, S. A. Lawal

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This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations.

Keywords: classification, data mining, decision tree, scholarship

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Authors: Ratun Rahman, Rafid Islam, Akin Ahmed, Kamrul Hasan, Hasan Mahmud

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Malware is becoming more prevalent, and several threat categories have risen dramatically in recent years. This paper provides a bird's-eye view of the world of malware analysis. The efficiency of five different machine learning methods (Naive Bayes, K-Nearest Neighbor, Decision Tree, Random Forest, and TensorFlow Decision Forest) combined with features picked from the retrieval of Android permissions to categorize applications as harmful or benign is investigated in this study. The test set consists of 1,168 samples (among these android applications, 602 are malware and 566 are benign applications), each consisting of 948 features (permissions). Using the permission-based dataset, the machine learning algorithms then produce accuracy rates above 80%, except the Naive Bayes Algorithm with 65% accuracy. Of the considered algorithms TensorFlow Decision Forest performed the best with an accuracy of 90%.

Keywords: android malware detection, machine learning, malware, malware analysis

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Authors: Ziwei Huang

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In order to promote Inventory development in Shenzhen, the market-oriented real estate development mode has occupied a dominant position in the urban renewal activities of Shenzhen. This research is based on the theory of role relationship and urban regime, taking the Mutoulong community as the research object. Carries on the case depth analysis found that: Under the situation of absence and dislocation of the government's role, land property rights disputes and lack of communication platforms is the main reason for the problems of nail households and market failures, and the long-term delay in the progress of old city reconstruction. Through the analysis of the cause of the transformation problem and the upper planning and interest coordination mechanism, the optimization strategy of the old city transformation is finally proposed as follows: the establishment of interest coordination platform, the risk assessment of the government's intervention in the preliminary construction of the land, the adaptive construction of laws and regulations, and the re-examination of the interest relationship between the government and the market.

Keywords: Shenzhen city, Mutoulong community, urban regeneration, urban regime theory, role relationship theory

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Authors: James Purnama, Riri Fitri Sari

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We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

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Authors: E. E. EL-Kholy, Ahamed Kalas, Mahmoud Fauzy, M. El-Shahat Dessouki, Abdou M. El-refay, Mohammed El-Zefery

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Direct Torque Control (DTC) is an AC drive control method especially designed to provide fast and robust responses. In this paper a progressive algorithm for direct torque control of three-phase induction drive system supplied by photovoltaic arrays using voltage source inverter to control motor torque and flux with maximum power point tracking at different level of insolation is presented. Experimental results of the new DTC method obtained by an experimental rapid prototype system for drives are presented. Simulation and experimental results confirm that the proposed system gives quick, robust torque and speed responses at constant switching frequencies.

Keywords: photovoltaic (PV) array, direct torque control (DTC), constant switching frequency, induction motor, maximum power point tracking (MPPT)

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Authors: O. Zimbili, W. Salim, M. Ndambuki

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Construction and Demolition (C&D) wastes contribute the highest percentage of wastes worldwide (75%). Furthermore, ceramic materials contribute the highest percentage of wastes within the C&D wastes (54%). The current option for disposal of ceramic wastes is landfill. This is due to unavailability of standards, avoidance of risk, lack of knowledge and experience in using ceramic wastes in construction. The ability of ceramic wastes to act as a pozzolanic material in the production of cement has been effectively explored. The results proved that temperatures used in the manufacturing of these tiles (about 900 ⁰C) are sufficient to activate pozzolanic properties of clay. They also showed that, after optimization (11-14% substitution), the cement blend performs better, with no morphological differences between the cement blended with ceramic waste, and that blended with other pozzolanic materials. Sanitary ware and electrical insulator porcelain wastes are some wastes investigated for usage as aggregates in concrete production. When optimized, both produced good results, better than when natural aggregates are used. However, the research on ceramic wastes as partial substitute for fine aggregates or cement has not been overly exploited as the other areas. This review has been concluded with focus on investigating whether ceramic wall tile wastes used as partial substitute for cement and fine aggregates could prove to be beneficial since the two materials are the most high-priced during concrete production.

Keywords: blended, morphological, pozzolanic, waste

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Authors: Shuo Liu, Dan Liu

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In the field of named entity recognition, most of the research has been conducted around simple entities. However, for nested named entities, which still contain entities within entities, it has been difficult to identify them accurately due to their boundary ambiguity. In this paper, a hierarchical recognition model is constructed based on the grammatical structure and semantic features of Chinese text for boundary calculation based on lexical features. The analysis is carried out at different levels in terms of granularity, semantics, and lexicality, respectively, avoiding repetitive work to reduce computational effort and using the semantic features of words to calculate the boundaries of entities to improve the accuracy of the recognition work. The results of the experiments carried out on web-based microblogging data show that the model achieves an accuracy of 86.33% and an F1 value of 89.27% in recognizing nested named entities, making up for the shortcomings of some previous recognition models and improving the efficiency of recognition of nested named entities.

Keywords: coarse-grained, nested named entity, Chinese natural language processing, word embedding, T-SNE dimensionality reduction algorithm

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Authors: Jeewan Rai, Kinzang, Yeshi Jigme Choden

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Accumulation of dust on solar panels impacts the overall efficiency and the amount of energy they produce. While various techniques exist for detecting dust to schedule cleaning, many of these methods use MATLAB image processing tools and other licensed software, which can be financially burdensome. This study will investigate the efficiency of a free open-source computer vision library using the YOLO algorithm. The proposed approach has been tested on images of solar panels with varying dust levels through an experiment setup. The experimental findings illustrated the effectiveness of using the YOLO-based image classification method and the overall dust detection approach with an accuracy of 90% in distinguishing between clean and dusty panels. This open-source solution provides a cost effective and accessible alternative to commercial image processing tools, offering solutions for optimizing solar panel maintenance and enhancing energy production.

Keywords: YOLO, openCV, dust detection, solar panels, computer vision, image processing

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Authors: Younus Mohammad, Anita B. Fallah, Ben J. Boyd, Shakila B. Rizwan

Abstract:

N-acylethanolamines (NAEs) are endogenous lipids, which have neuromodulatory properties. NAEs have shown neuroprotective properties in various neurodegenerative diseases including Alzheimer's disease, Parkinson's disease and ischemic stroke. However, NAEs are eliminated rapidly in vivo by enzymatic hydrolysis. We propose to encapsulate NAEs in liquid crystalline nanoparticles (cubosomes) to increase their biological half-life and explore their therapeutic potential. Recently, we have reported the co-formulation and nanostructural characterization of cubosomes containing the NAE, oleoylethanolamide and a synthetic cubosome forming lipid phytantriol. Here, we report on the formulation of cubosomes with the NAE, linoleoylethanolamide (LEA) as the core cubosome forming lipid. LEA-cubosomes were formulated in the presence of three different steric stabilisers: two brain targeting ligands, Tween 80 and Pluronic P188 and a control, Pluronic F127. Size, morphology and internal structure of formulations were characterized by dynamic light scattering (DLS), cryogenic transmission electron microscopy (Cryo–TEM) and small angle X–ray scattering (SAXS), respectively. Chemical stability of LEA in formulations was investigated using high-performance liquid chromatography (HPLC). Cytotoxicity of formulations towards human cerebral microvascular endothelial cell line (hCMEC/D3) was also investigated using an MTT (3-[4, 5- dimethylthiazol-2-yl]-2, 5-diphenyl tetrazolium bromide) assay. All cubosome formulations had mean particle size of less than 250 nm and were uniformly distributed with polydispersity indices less than 0.2. Cubosomes produced had a bicontinuous cubic internal structure with an Im3m space group but different lattice parameters, indicating the different modes of interaction between the stabilisers and LEA. LEA in formulations was found to be chemically stable. At concentrations of up to 20 µg/mL LEA in the presence of all the stabilisers, greater than 80% cell viability was observed.

Keywords: blood-brain barrier, cubosomes, linoleoyl ethanolamide, N-acylethanolamines (NAEs)

Procedia PDF Downloads 202

Authors: A. Shahsavari, M. Nili-Ahmadabadi

Abstract:

This paper presents an innovative one-dimensional optimization of a transonic compressor based on the radial equilibrium theory by means of increasing blade loading. Firstly, the rotor blade of the transonic compressor is redesigned based on the constant span-wise deHaller number and diffusion. The code is applied to extract compressor meridional plane and blade to blade geometry containing rotor and stator in order to design blade three-dimensional view. A structured grid is generated for the numerical domain of fluid. Finer grids are used for regions near walls to capture boundary layer effects and behavior. RANS equations are solved by finite volume method for rotating zones (rotor) and stationary zones (stator). The experimental data, available for the performance map of NASA Rotor67, is used to validate the results of simulations. Then, the capability of the design method is validated by CFD that is capable of predicting the performance map. The numerical results of new geometry show about 19% increase in pressure ratio and 11% improvement in overall efficiency of the transonic stage; however, the design point mass flow rate of the new compressor is 5.7% less than that of the original compressor.

Keywords: deHaller number, one dimensional design, radial equilibrium, transonic compressor

Procedia PDF Downloads 338

Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

Abstract:

Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: feature generation, feature learning, genetic algorithm, music information retrieval

Procedia PDF Downloads 433