Search results for: one side class algorithm

Authors: Sikander Singh Cheema, Jasmeen Kaur

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In this paper, the concept of data mining is summarized and its one of the important process i.e KDD is summarized. The data mining based on Genetic Algorithm is researched in and ways to achieve the data mining Genetic Algorithm are surveyed. This paper also conducts a formal review on the area of data mining tasks and genetic algorithm in various fields.

Keywords: data mining, KDD, genetic algorithm, descriptive mining, predictive mining

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Authors: Chi-Lun Liu

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Requirements modeling and analysis are important in successful information systems' maintenance. Unified Modeling Language (UML) class diagrams are useful standards for modeling information systems. To our best knowledge, there is a lack of a systems development methodology described by the organism metaphor. The core concept of this metaphor is adaptation. Using the knowledge representation and reasoning approach and ontologies to adopt new requirements are emergent in recent years. This paper proposes an organic methodology which is based on constructivism theory. This methodology is a knowledge representation and reasoning approach to analyze new requirements in the class diagrams maintenance. The process and rules in the proposed methodology automatically analyze inconsistencies in the class diagram. In the big data era, developing an automatic tool based on the proposed methodology to analyze large amounts of class diagram data is an important research topic in the future.

Keywords: knowledge representation, reasoning, ontology, class diagram, software engineering

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Authors: Wiseborn Manfe Danquah, D. Turgay Altilar

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Vehicular Ad-hoc Network (VANET) is an integral component of Intelligent Transport Systems (ITS) that has enjoyed a lot of attention from the research community and the automotive industry. This is mainly due to the opportunities and challenges it presents. Vehicular Ad-hoc Network being a class of Mobile Ad-hoc Networks (MANET) has all the security concerns existing in traditional MANET as well as new security and privacy concerns introduced by the unique vehicular communication environment. This paper provides a survey of the possible attacks in vehicular environment, as well as security and privacy concerns in VANET. It also provides an insight into the development of a comprehensive cloud framework to provide a more robust and secured communication among vehicular nodes and road side units. Our proposal, a Metropolitan Based Public Interconnected Vehicular Cloud (MIVC) infrastructure seeks to provide a more reliable and secured vehicular communication network.

Keywords: mobile Ad-hoc networks, vehicular ad hoc network, cloud, ITS, road side units (RSU), metropolitan interconnected vehicular cloud (MIVC)

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Authors: Hui Liu, Xiaozan Wang, Jiarong Zhong, Ziming Shao

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Introduction: Related research shows that students don’t concentrate on teacher’s speaking in the classroom. The d2 attention test is a time-limited test about selective attention. The d2 attention test can be used to evaluate individual selective attention. Purpose: To use the d2 attention test tool to measure the difference between the attention level of the experimental class and the control class before and after Brain-Break and to explore the effect of Brain-Break in the classroom on students' selective attention. Methods: According to the principle of no difference in pre-test data, two classes in the fourth- grade of Shenzhen Longhua Central Primary School were selected. After 20 minutes of class in the third class in the morning and the third class in the afternoon, about 3-minute Brain-Break intervention was performed in the experimental class for 10 weeks. The normal class in the control class did not intervene. Before and after the experiment, the d2 attention test tool was used to test the attention level of the two-class students. The paired sample t-test and independent sample t-test in SPSS 23.0 was used to test the change in the attention level of the two-class classes around 10 weeks. This article only presents results with significant differences. Results: The independent sample t-test results showed that after ten-week of Brain-Break, the missed errors (E1 t = -2.165 p = 0.042), concentration performance (CP t = 1.866 p = 0.05), and the degree of omissions (Epercent t = -2.375 p = 0.029) in experimental class showed significant differences compared with control class. The students’ error level decreased and the concentration increased. Conclusions: Adding Brain-Break interventions in the classroom can effectively improve the attention level of fourth-grade primary school students to a certain extent, especially can improve the concentration of attention and decrease the error rate in the tasks. The new sport's learning model is worth promoting

Keywords: cultural class, micromotor, attention, D2 test

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Authors: Jehad Al Dallal

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Class cohesion is a key object-oriented software quality attribute that is used to evaluate the degree of relatedness of class attributes and methods. Researchers have proposed several class cohesion measures. However, the effect of considering the special methods (i.e., constructors, destructors, and access and delegation methods) in cohesion calculation is not thoroughly theoretically studied for most of them. In this paper, we address this issue for three popular connectivity-based class cohesion measures. For each of the considered measures we theoretically study the impact of including or excluding special methods on the values that are obtained by applying the measure. This study is based on analyzing the definitions and formulas that are proposed for the measures. The results show that including/excluding special methods has a considerable effect on the obtained cohesion values and that this effect varies from one measure to another. For each of the three connectivity-based measures, the proposed theoretical study recommended excluding the special methods in cohesion measurement.

Keywords: object-oriented class, software quality, class cohesion measure, class cohesion, special methods

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Authors: F. Erdal, E. Dogan, F. E. Uz

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In this study, firefly optimization based optimum design algorithm is presented for the grillage systems. Naming of the algorithm is derived from the fireflies, whose sense of movement is taken as a model in the development of the algorithm. Fireflies’ being unisex and attraction between each other constitute the basis of the algorithm. The design algorithm considers the displacement and strength constraints which are implemented from LRFD-AISC (Load and Resistance Factor Design-American Institute of Steel Construction). It selects the appropriate W (Wide Flange)-sections for the transverse and longitudinal beams of the grillage system among 272 discrete W-section designations given in LRFD-AISC so that the design limitations described in LRFD are satisfied and the weight of the system is confined to be minimal. Number of design examples is considered to demonstrate the efficiency of the algorithm presented.

Keywords: firefly algorithm, steel grillage systems, optimum design, stochastic search techniques

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Authors: Alfrina Marwan, Erna Sulistyawati

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Class III malocclusion shows both skeletal and dentoalveolar component. Sketal Class III malocclusion can have variants in different region, maxilla or mandibular. Skeletal Class III malocclusion during growth period is considered to treat to prevent its severity in adulthood. Orthopedics treatment of skeletal Class III malocclusion in growing patient can be treated by using reverse twin block with expansion screw to modify the growth pattern. The objective of this case report was to describe the functional correction of skeletal Class III maloclussion using reverse twin block with expansion screw in growing patient. A patient with concave profile came with a chief complaint of aesthetic problems. The cephalometric analysis showed that patient had skeletal Class III malocclusion (ANB -5⁰, SNA 75º, Wits appraisal -3 mm) with anterior cross bite and deep bite (overjet -3 mm, overbite 6 mm). In this case report, the patient was treated with reverse twin block appliance with expansion screw. After three months of treatment, the skeletal problems have been corrected (ANB -1°), overjet, overbite and aesthetic were improved. Reverse twin block appliance with expansion screw can be used as orthopedics treatment for skeletal Class III malocclusion in growing patient and can improve the aesthetic with great satisfaction which was the main complaint in this patient.

Keywords: maxilla retrognatism, reverse twin block, skeletal class III malocclusion, growing patient

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Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

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Authors: Yuqing Sun

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Nowadays, English has been taught in many countries as a second language. One of the major ways to learn this language is through the class teaching. As in the field of second language acquisition, there are many factors to affect its acquisition processes, such as the target language itself, a learner’s personality, cognitive factor, language transfer, and the outward factors (teaching method, classroom, environmental factor, teaching policy, social environment and so on). Flipped Classroom as a newly developed classroom model has been widely used in language teaching classroom, which was, to some extent, accepted by teachers and students for its effect. It distinguishes itself from the traditional classroom for its focus on the learner and its great importance attaching to the personal learning process and the application of technology. The class becomes discussion-targeted, and the class order is somewhat inverted since the teaching process is carried out outside the class, while the class is only for knowledge-internalization. This paper will concentrate on the influences of the flipped classroom, as a classroom affecting factor, on the the process of English acquisition by the way of case studies (English teaching class in China), and the analysis of the mechanism of the flipped classroom itself to propose some feasible advice of promoting the the effectiveness of English acquisition.

Keywords: second language acquisition, English, flipped classroom, case

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Authors: Tahar Djebbar Aziza

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The American society, like all societies, is fractured by social divisions between different groups of people. It is divided by race, class, gender, and other social and cultural characteristics. Social divisions affect the way and the manner welfare is delivered for citizens within the American society. The welfare state exists to guarantee the promotion of well –being for all the different components within a society without taking into account their age, gender, their ethnicity/race, or their social belonging (class). Race, class, and even gender issues are the main factors that affected the formal structure, the nature, as well as the evolution of the American welfare state and led to its uniqueness. They have affected the structure and the evolution of the American welfare state since its creation in the 1930s, and led to its uniqueness in an international level. This study aims therefore at enhancing the readers’ awareness of social divisions: race, class, gender and their implications for the distribution of welfare resources and life chances in the USA from the early 1930s to the late 1990s.

Keywords: African Americans, class, gender, minority groups, race, social divisions, social policy, U.S. welfare state

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Authors: Yan Pang, Xiang Wang, Zhaomiao Liu

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Droplet microfluidics, in which nanoliter to picoliter droplets acted as individual compartments, are common to a diverse array of applications such as analytical chemistry, tissue engineering, microbiology and drug discovery. The droplet generation in a simplified two dimension T-shape microchannel with the main channel width of 50 μm and the side channel width of 25 μm, is simulated to investigate effects of the forced fluctuation of the side wall on the droplet generation and flow. The periodic fluctuations are applied on a length of the side wall in the main channel of the T-junction with the deformation shape of the double-clamped beam acted by the uniform force, which varies with the flow time and fluctuation periods, forms and positions. The fluctuations under most of the conditions expand the distribution range of the droplet size but have a little effect on the average size, while the shape of the fixed side wall changes the average droplet size chiefly. Droplet sizes show a periodic pattern along the relative time when the fluctuation is forced on the side wall near the T-junction. The droplet emerging frequency is not varied by the fluctuation of the side wall under the same flow rate and geometry conditions. When the fluctuation period is similar with the droplet emerging period, the droplet size shows a nice stability as the no fluctuation case.

Keywords: droplet generation, droplet size, flow flied, forced fluctuation

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Authors: A. B. M. Najmus Sakib

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Being one of the most densely populated cities in the world, Dhaka is facing diversified types of crimes every day. Limitations of resources insert serious strains among the inhabitants of this city. This paper aims to analyze the correlation between crime and class, more especially the violent crime in connection with social class. Following the stratified random sampling technique, one of the police divisions among eight of the Dhaka Metropolitan Police (DMP) will be selected. The data will be collected by evaluating the case files found in the police report. First, this paper discusses the nature and pattern of violent crimes in Dhaka city. Then, it assesses the socio-economic status of the accused persons considering their professions. Furthermore, by testing hypothesis, it will identify how the social classes are connected with violent crimes. Finally, the paper will ascertain the particular class that has an impact on violent crime in Dhaka City and will be ended by suggesting possible measures should take by the law enforcement agencies of Bangladesh.

Keywords: social class, violent crime, crime prevention, nature of crime

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Authors: Roshanak Khodabakhsh Jolfaei, Javad Akbari Torkestani

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As a cooperative environment for problem-solving, it is necessary that grids develop efficient job scheduling patterns with regard to their goals, domains and structure. Since the Grid environments facilitate distributed calculations, job scheduling appears in the form of a critical problem for the management of Grid sources that influences severely on the efficiency for the whole Grid environment. Due to the existence of some specifications such as sources dynamicity and conditions of the network in Grid, some algorithm should be presented to be adjustable and scalable with increasing the network growth. For this purpose, in this paper a job scheduling algorithm has been presented on the basis of learning automata in computational Grid which the performance of its results were compared with FPSO algorithm (Fuzzy Particle Swarm Optimization algorithm) and GJS algorithm (Grid Job Scheduling algorithm). The obtained numerical results indicated the superiority of suggested algorithm in comparison with FPSO and GJS. In addition, the obtained results classified FPSO and GJS in the second and third position respectively after the mentioned algorithm.

Keywords: computational grid, job scheduling, learning automata, dynamic scheduling

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Authors: M. Laura Vazquez Maggio, Lilia Dominguez Villalobos, Jan Luka Frey

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This paper contributes to the understanding of the dynamic and the relational nature of identities formation among skilled middle-class migrants. Following the idea that identities are never singular, multifaceted and have a necessarily processual character, the authors specifically analyze three dimensions of the identity of qualified Mexican migrants in the US and the interplay between them. Drawing on semi-structured interviews with skilled Mexican middle-class migrants in the US, the paper explores how skilled Mexican migrants preserve their ethno-national identity (their ‘Mexicanness’) in reaction to a hostile socio-political reception context in the US. It further shows how these migrants recreate their class identity and show tendencies to distance themselves from what they perceive as lower-class Mexican migrants and the dominant popular Mexican and Latin-American cultural expressions. In a final step, it examines how the lived experience of migration itself impacts the migrants’ identities, their concept of self and feelings/modes of being and belonging.

Keywords: ethno-national identity, middle class identity, middle-class migration, migrants’ identity, skilled migration

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Authors: Sultan Noman Qasem

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This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFNN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: radial basis function network, hybrid learning, multi-objective optimization, genetic algorithm

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid Tabu Search (TS) algorithm is suggested for the multi-objective job shop scheduling problems (MO-JSSPs). The algorithm integrates several shifting bottleneck based neighborhood structures with the Giffler & Thompson algorithm, which improve efficiency of the search. Diversification and intensification are provided with local and global left shift algorithms application and also new semi-active, active, and non-delay schedules creation. The suggested algorithm is tested in the MO-JSSPs benchmarks from the literature based on the Pareto optimality concept. Different performances criteria are used for the multi-objective algorithm evaluation. The proposed algorithm is able to find the Pareto solutions of the test problems in shorter time than other algorithm of the literature.

Keywords: tabu search, heuristics, job shop scheduling, multi-objective optimization, Pareto optimality

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Authors: Alireza Lavaei, Alireza Lohrasbi, Mohammadali M. Shahlaei

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To reduce the overall time of structural optimization for earthquake loads two strategies are adopted. In the first strategy, a neural system consisting self-organizing map and radial basis function neural networks, is utilized to predict the time history responses. In this case, the input space is classified by employing a self-organizing map neural network. Then a distinct RBF neural network is trained in each class. In the second strategy, an improved genetic algorithm is employed to find the optimum design. A 72-bar space truss is designed for optimal weight using exact and approximate analysis for the El Centro (S-E 1940) earthquake loading. The numerical results demonstrate the computational advantages and effectiveness of the proposed method.

Keywords: optimization, genetic algorithm, neural networks, self-organizing map

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Authors: Daniel Bulanda, Janusz A. Starzyk, Adrian Horzyk

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The electrocardiogram (ECG) is one of the most commonly used medical tests, essential for correct diagnosis and treatment of the patient. While ECG devices generate a huge amount of data, only a small part of them carries valuable medical information. To deal with this problem, many compression algorithms and filters have been developed over the past years. However, the rapid development of new machine learning techniques poses new challenges. To address this class of problems, we created the FlexPoints algorithm that searches for characteristic points on the ECG signal and ignores all other points that do not carry relevant medical information. The conducted experiments proved that the presented algorithm can significantly reduce the number of data points which represents ECG signal without losing valuable medical information. These sparse but essential characteristic points (flex points) can be a perfect input for some modern machine learning models, which works much better using flex points as an input instead of raw data or data compressed by many popular algorithms.

Keywords: characteristic points, electrocardiogram, ECG, machine learning, signal compression

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Authors: Qaisar Fraz, H. M. Jafar, Mojeeb Bin Ihsan

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This paper presents simulation and experimen-tal results for wide band U-shaped side slots loaded linearly polarized rectangular microstrip antenna with broad side radiation characteristics suitable for onboard applications. The structure has been evolved in rugged and compact form to make it suitable for on-board applications. In addition to U-shaped central slot, pair of parallel narrow slots has been embedded close to non-radiating edges. The size and shape of these side slots have been optimized to improve the matching at upper frequency of the band. The impedance bandwidth of 34.8% as compared to 2-5% bandwidth of conventional microstrip antenna has been achieved. The frequency ratio of the two well-matched operating sections is found to be f2 / f1=1.33. The experimental results are in good agreement with the numerical results.

Keywords: low profile antennas, u-slot antennas, broad band antennas, broad-side radiation pattern, high gain antennas

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Authors: Karen Bell

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It is vital to integrate a working-class perspective into the just transition to an inclusive and sustainable society because of the particular expertise and interests that working-class people bring to the debates and actions. In class societies, those who are not well represented in the current structures of power can find it easier to see when the system is not working. They are also more likely to be impacted by the environmental crises because wealthier people can change their dwelling places, jobs and other aspects of their lives in the face of risks. Therefore, challenging the ‘post-material values thesis’, this paper argues that, if enabled to do so, working-class people are more likely to identify what needs to be addressed and changed in transition and can be more motivated to make the changes necessary than other social groups. However, they are often excluded from environmental decision-making and environmental social movements. The paper is based on a mixed methodology; drawing on secondary data, interview material, participant observation and documentary analysis. It is based on years of research and activism on environmental issues in working-class communities. The analysis and conclusion discusses the seven kinds of change required to address this problem: 1) organizational change - participatory practice (2) legislative change - make class an equalities and human rights issue (3) policy change - reduce inequality (4) social movement change - radicalize the environmental movement and support the environmental working-class (5) political change - create an eco-social state based on sharing (6) cultural change - integrate social and environmental justice, and (7) revolutionary change - dismantle capitalism.

Keywords: environmentalism, just transition, sustainability, working class

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Authors: Yi-Cheng Tian, Miin-Shen Yang

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The mixture likelihood approach to clustering is a popular clustering method where the expectation and maximization (EM) algorithm is the most used mixture likelihood method. In the literature, the EM algorithm had been used for mixture regression models. However, these EM mixture regression algorithms are sensitive to initial values with a priori number of clusters. In this paper, to resolve these drawbacks, we construct a learning-based schema for the EM mixture regression algorithm such that it is free of initializations and can automatically obtain an approximately optimal number of clusters. Some numerical examples and comparisons demonstrate the superiority and usefulness of the proposed learning-based EM mixture regression algorithm.

Keywords: clustering, EM algorithm, Gaussian mixture model, mixture regression model

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

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

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

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Authors: Nursuhaila Ibrahim, Noor Hanim Rahmat, Nurul Ain Hasni, Nursyuhada Zakaria

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Past studies have shown that class discussions in the ESL classrooms not only helped students exchange ideas with their peers. Students also learn turn taking skills throughout the discussion. Through interacting with their peers, learners learn to use turn-taking strategies. They learn to wait for their turn, to listen to the ideas of others, to disagree, or to agree, and to add on more points in the conversation. This quantitative research explores students’ perception on class discussions and how the discussions influence their choice of turn-taking strategies. Findings of this research will have interesting implications towards the use of class discussions in the ESL classrooms.

Keywords: ESL, class discussions, turn-taking skills, peers

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Authors: Emilija Tribocka

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This contribution presents parts of an ongoing study of a diachronic relationship between two weak verb classes in Norwegian, the a-class (cf. the paradigm of ‘throw’: kasta – kastar – kasta – kasta) and the e-class (cf. the paradigm of ‘buy’: kjøpa – kjøper – kjøpte – kjøpt). The study investigates inflection class shifts between the two classes with Old Norse, the ancestor of Modern Norwegian, as a starting point. Examination of inflection in 38 verbs in four chosen dialect areas (106 places of attestations) demonstrates that the shifts from the a-class to the e-class are widespread to varying degrees in three out of four investigated areas and are more common than the shifts in the opposite direction. The diachronic productivity of the e-class is unexpected for several reasons. There is general agreement that type frequency is an important factor influencing productivity. The a-class (53% of all weak verbs) was more type frequent in Old Norse than the e-class (42% of all weak verbs). Thus, given the type frequency, the expansion of the e-class is unexpected. Furthermore, in the ‘core’ areas of expanded e-class inflection, the shifts disregard phonological principles creating forms with uncomfortable consonant clusters, e.g., fiskte instead of fiska, the preterit of fiska ‘fish’. Later on, these forms may be contracted, i.e., fiskte > fiste. In this contribution, two factors influencing the shifts are presented: phonological form and token frequency. Verbs with the stem ending in a consonant cluster, particularly when the cluster ends in -t, hardly ever shift to the e-class. As a matter of fact, verbs with this structure belonging to the e-class in Old Norse shift to the a-class in Modern Norwegian, e.g., ON e-class verb skipta ‘change’ shifts to the a-class. This shift occurs as a result of the lack of morpho-phonological transparency between the stem and the preterit suffix of the e-class, -te. As there is a phonological fusion between the stem ending in -t and the suffix beginning in -t, the transparent a-class inflection is chosen. Token frequency plays an important role in the shifts, too, in some dialects. In one of the investigated areas, the most token frequent verbs of the ON e-class remain in the e-class (e.g., høyra ‘hear’, leva ‘live’, kjøpa ‘buy’), while less frequent verbs may shift to the a-class. Furthermore, the results indicate that the shift from the a-class to the e-class occurs in some of the most token frequent verbs of the ON a-class in this area, e.g., lika ‘like’, lova ‘promise’, svara ‘answer’. The latter is unexpected as frequent items tend to remain stable. This study presents a case of unexpected productivity, demonstrating that minor patterns can grow and outdo major patterns. Thus, type frequency is not the only factor that determines productivity. The study addresses the role of phonological form and token frequency in the spread of inflection patterns.

Keywords: inflection class, productivity, token frequency, phonological form

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Authors: Jamaludin Sallim, Rozlina Mohamed, Roslina Abdul Hamid

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In this paper, we proposed an Ant Colony Optimization (ACO) algorithm together with Traveling Salesman Problem (TSP) approach to investigate the clustering problem in Protein Interaction Networks (PIN). We named this combination as ACOPIN. The purpose of this work is two-fold. First, to test the efficacy of ACO in clustering PIN and second, to propose the simple generalization of the ACO algorithm that might allow its application in clustering proteins in PIN. We split this paper to three main sections. First, we describe the PIN and clustering proteins in PIN. Second, we discuss the steps involved in each phase of ACO algorithm. Finally, we present some results of the investigation with the clustering patterns.

Keywords: ant colony optimization algorithm, searching algorithm, protein functional module, protein interaction network

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Authors: Zayar Phyo, Ei Chaw Htoon

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In a New-LSB based Steganography method, the Fisher-Yates algorithm is used to permute an existing array randomly. However, that algorithm performance became slower and occurred memory overflow problem while processing the large dimension of images. Therefore, the Text-Based Shuffling algorithm aimed to select only necessary pixels as hiding characters at the specific position of an image according to the length of the input text. In this paper, the enhanced text-based shuffling algorithm is presented with the powered of GPU to improve more excellent performance. The proposed algorithm employs the OpenCL Aparapi framework, along with XORShift Kernel including the Pseudo-Random Number Generator (PRNG) Kernel. PRNG is applied to produce random numbers inside the kernel of OpenCL. The experiment of the proposed algorithm is carried out by practicing GPU that it can perform faster-processing speed and better efficiency without getting the disruption of unnecessary operating system tasks.

Keywords: LSB based steganography, Fisher-Yates algorithm, text-based shuffling algorithm, OpenCL, XORShiftKernel

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Authors: Noboru Abe, Yoshinori Amai, Toshinori Nakatake, Sumio Masuda, Kazuaki Yamaguchi

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We consider the problem of placing labels of the points on a plane. For each point, its position, the size of its label and a priority are given. Moreover, several candidates of its label positions are prespecified, and each of such label positions is assigned a priority. The objective of our problem is to maximize the total sum of priorities of placed labels and their points. By refining a labeling algorithm that can use these priorities, we propose a new heuristic algorithm which is more suitable for treating the assigned priorities.

Keywords: map labeling, greedy algorithm, heuristic algorithm, priority

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Authors: Ilma Robo, Saimir Heta, Emela Dalloshi, Nevila Alliu, Vera Ostreni

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The dental whitening process, beyond the fact that it is a mini-invasive dental treatment, has effects on the dental structure, or on the pulp of the tooth, where it is applied. The electronic search was performed using keywords to find articles published within the last 10 years about side effects, assessed as such, of minimally invasive dental bleaching treatment. Methodology: In selected articles, the other aim of the study was to evaluate the side effects of bleaching based on the percentage and type of solution used, where the latter was evaluated on the basic solution used for bleaching. Results: The side effects of bleaching are evaluated in selected articles depending on the method of bleaching application, which means it is carried out with recommended solutions, or with mixtures of alternative solutions or substances based on Internet information. Short conclusion: The dental bleaching process has side effects which have not yet been definitively evaluated, experimentally in large samples of individuals or animals (mice or cattle) to arrive at accurate numerical conclusions. The trend of publications about this topic is increasing in recent years, as long as the trend for aesthetic facial treatments, including dental ones, is increasing.

Keywords: teeth whitening, side effects, permanent teeth, formed dental apex

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Authors: Yongfang Deng, Dunwen Zuo

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An attempt is made here to join 2024 aluminum alloy plate by friction stir joining (FSJ) using different types of tools. Joint surface morphology was observed, and both arc line spacing and flash were measured. Study is carried out on the effect of pin, shoulder and eccentricity of the tool on the surface topography of the joint and the formation of the joint surface topography is analyzed. It is found that, eccentric squeezing action of the tool is the mainly motive power to form arc lines contour and flash structure. Little flash appears in the advancing side but with severe deformation, while the flash in the retreating side is heavy but with soft deformation. The pin of tool has a deep impact on the flash on the advancing side of the joints. Shoulder can widen the arc lines, refine arcs structure, reduce flash in the retreat side, but will increase the flash in the advancing side. Increasing the amount of eccentricity, it has litter effect on the arc line spacing but will destroy the arc lines morphology in the joint surface and promote the formation of filamentous flash structure in the joint.

Keywords: FSJ, surface morphology, tool, joint

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Authors: Abigail Qian Zhou

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In today's China, the well-educated middle class, with stable jobs and above-average income, are the driving force behind its Internet society. Through the analysis of data from the 2015 Chinese General Social Survey and 50 interviewees, this study investigates the current situation of this group’s specific internet usage. The findings of this study demonstrate that daily life among the members of this socioeconomic group is closely tied to the Internet. For Chinese middle class, the Internet is used to socialize and entertain self and others. It is also used to search for and share information as well as to build their identities. The empirical results of this study will provide a reference, supported by factual data, for enterprises seeking to target the Chinese middle class through online marketing efforts.

Keywords: middle class, Internet use, network behaviour, online marketing, China

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