Search results for: λ-statistical cluster points

Authors: M. H. M. Rashid

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A Banach space operator T obeys property (gm) if the isolated points of the spectrum σ(T) of T which are eigenvalues are exactly those points λ of the spectrum for which T − λI is a left Drazin invertible. In this article, we study the stability of property (gm), for a bounded operator acting on a Banach space, under perturbation by finite rank operators, by nilpotent operators, by quasi-nilpotent operators, or more generally by algebraic operators commuting with T.

Keywords: Weyl's Theorem, Weyl Spectrum, Polaroid operators, property (gm)

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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: M. Saeed, A. Shahidzadeh

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Interaction between teachers and learners requires applying a set of samples (examples) which helps to create coordination between the goals and methods. The main result and achievement and application of samples (examples) are that they can bring the teacher and learner to a shared understanding of the concept. mathematical concepts, and also one of the challenging issues in the discussion of the function is to find the collision points of functions of and, regarding that the example space of teachers is different in this issue, this paper aims to present an example space including several problems of the secondary school with the help of intuition and drawing various graphs of functions of and for more familiarity of teachers.

Keywords: inverse function, educational example, Mathematic example, example space

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Authors: Vineetha Bettaiah, Heggere S. Ranganath

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This paper presents a Hierarchical Piecewise Linear Approximation (HPLA) for the representation of time series data in which the time series is treated as a curve in the time-amplitude image space. The curve is partitioned into segments by choosing perceptually important points as break points. Each segment between adjacent break points is recursively partitioned into two segments at the best point or midpoint until the error between the approximating line and the original curve becomes less than a pre-specified threshold. The HPLA representation achieves dimensionality reduction while preserving prominent local features and general shape of time series. The representation permits course-fine processing at different levels of details, allows flexible definition of similarity based on mathematical measures or general time series shape, and supports time series data mining operations including query by content, clustering and classification based on whole or subsequence similarity.

Keywords: data mining, dimensionality reduction, piecewise linear representation, time series representation

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Authors: Ebrahim Farahmand, Ali Mahani

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Wireless sensor networks (WSNs) can facilitate continuous monitoring of patients and increase early detection of emergency conditions and diseases. High density WSNs helps us to accurately monitor a remote environment by intelligently combining the data from the individual nodes. Due to energy capacity limitation of sensors, enhancing the lifetime and the reliability of WSNs are important factors in designing of these networks. The clustering strategies are verified as effective and practical algorithms for reducing energy consumption in WSNs and can tackle WSNs limitations. In this paper, an Energy-efficient weight-based Clustering Protocol (EWCP) is presented. Artificial retina is selected as a case study of WSNs applied in body sensors. Cluster heads’ (CHs) selection is equipped with energy efficient parameters. Moreover, cluster members are selected based on their distance to the selected CHs. Comparing with the other benchmark protocols, the lifetime of EWCP is improved significantly.

Keywords: WSN, healthcare monitoring, weighted based clustering, lifetime

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Authors: Chia-Yen Lee, Hao-Jen Wang, Jhih-Hao Lai

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In recent years, infrared (IR) imaging has been considered as a potential tool to assess the efficacy of chemotherapy and early detection of breast cancer. Regions of tumor growth with high metabolic rate and angiogenesis phenomenon lead to the high temperatures. Observation of differences between the heat maps in long term is useful to help assess the growth of breast cancer cells and detect breast cancer earlier, wherein the multi-time infrared image alignment technology is a necessary step. Representative feature points detection and matching are essential steps toward the good performance of image registration and quantitative analysis. However, there is no clear boundary on the infrared images and the subject's posture are different for each shot. It cannot adhesive markers on a body surface for a very long period, and it is hard to find anatomic fiducial markers on a body surface. In other words, it’s difficult to detect and match features in an IR sequence images. In this study, automated feature detection and matching algorithms with two type of automatic feature points (i.e., vascular branch points and modified Harris corner) are developed respectively. The preliminary results show that the proposed method could identify the representative feature points on the IR breast images successfully of 98% accuracy and the matching results of 93% accuracy.

Keywords: Harris corner, infrared image, feature detection, registration, matching

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Authors: Nermeen El Kashef, Yasser Fouad, Khaled Mahar

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No AI-complete system can model the human brain or behavior, without looking at the totality of the whole situation and incorporating a combination of senses. This paper proposes a Pattern Recognition model based on Simulation of Chemical Senses (SCS) for separation and classification of sign language. The model based on human taste controlling strategy. The main idea of the introduced model is motivated by the facts that the tongue cluster input substance into its basic tastes first, and then the brain recognizes its flavor. To implement this strategy, two level architecture is proposed (this is inspired from taste system). The separation-level of the architecture focuses on hand posture cluster, while the classification-level of the architecture to recognizes the sign language. The efficiency of proposed model is demonstrated experimentally by recognizing American Sign Language (ASL) data set. The recognition accuracy obtained for numbers of ASL is 92.9 percent.

Keywords: artificial intelligence, biocybernetics, gustatory system, sign language recognition, taste sense

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Authors: Sahar Elsaleh, Ghada Farhat, Shaikha Al-Derham, Fasih Alam

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Background: Cesarean section (CS) delivery is one of the major concerns both in developing and developed countries. The rate of CS deliveries are on the rise globally, and especially in Qatar. Many socio-economic, demographic, clinical and institutional factors play an important role for cesarean sections. This study aims to investigate factors affecting the prevalence of CS among women in Qatar using the UNICEF’s Multiple Indicator Cluster Survey (MICS) 2012 database. Methods: The study has focused on the women’s questionnaire of the MICS, which was successfully distributed to 5699 participants. Following study inclusion and exclusion criteria, a final sample of 761 women aged 19- 49 years who had at least one delivery of giving birth in their lifetime before the survey were included. A number of socio-economic, demographic, clinical and institutional factors, identified through literature review and available in the data, were considered for the analyses. Bivariate and multivariate logistic regression models, along with a multi-level modeling to investigate clustering effect, were undertaken to identify the factors that affect CS prevalence in Qatar. Results: From the bivariate analyses the study has shown that, a number of categorical factors are statistically significantly associated with the dependent variable (CS). When identifying the factors from a multivariate logistic regression, the study found that only three categorical factors -‘age of women’, ‘place at delivery’ and ‘baby weight’ appeared to be significantly affecting the CS among women in Qatar. Although the MICS dataset is based on a cluster survey, an exploratory multi-level analysis did not show any clustering effect, i.e. no significant variation in results at higher level (households), suggesting that all analyses at lower level (individual respondent) are valid without any significant bias in results. Conclusion: The study found a statistically significant association between the dependent variable (CS delivery) and age of women, frequency of TV watching, assistance at birth and place of birth. These results need to be interpreted cautiously; however, it can be used as evidence-base for further research on cesarean section delivery in Qatar.

Keywords: cesarean section, factors, multiple indicator cluster survey, MICS database, Qatar

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Authors: M. Bahgat, H. A. Hanafy, S. Lakdawala

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Clustering phenomenon of pellets was observed frequently in shaft processes operating at higher temperatures. Clustering is a result of the growth of fibrous iron precipitates (iron whiskers) that become hooked to each other and finally become crystallized during the initial stages of metallization. If the pellet clustering is pronounced, sometimes leads to blocking inside the furnace and forced shutdown takes place. This work clarifies further the relation between metallic iron whisker growth and iron ore mineralogy. Various pellet sizes (6 – 12.0 & +12.0 mm) from three different ores (A, B & C) were (completely and partially) reduced at 985 ^oC with H₂/CO gas mixture using thermos-gravimetric technique. It was found that reducibility increases by decreasing the iron ore pellet’s size. Ore (A) has the highest reducibility than ore (B) and ore (C). Increasing the iron ore pellet’s size leads to increase the probability of metallic iron whisker formation. Ore (A) has the highest tendency for metallic iron whisker formation than ore (B) and ore (C). The reduction reactions for all iron ores A, B and C are mainly controlled by diffusion reaction mechanism.

Keywords: shaft furnace, cluster, metallic iron whisker, mineralogy, ferrous metallurgy

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Authors: Gaye Demi̇rtaş Adli

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Research: It was conducted to determine the factors affecting the fear of self-injection and self-pricking of fingers of diabetic individuals.The study was conducted as a cross-sectional, relation-seeking, and descriptive study. The study was conducted on 122 patients who had just started insulin therapy. Data were obtained through The Descriptive Patient Form, The Diabetic Self-Injection, and the Fear of Testing Questionnaire Form (D-FISQ). Descriptive statistical methods used in the evaluation of data are the Mann-Whitney U test, Kruskal-Wallis H test, and the Spearman correlation. The factors affecting the scale scores were evaluated with multiple linear regression analysis. The value of P<0.05 was considered statistically significant. Study group: 56.6% of the patients are male patients. Fear of self-injection (injection), fear of self-testing (test), and total fear (total) scores of women were found to be statistically higher than men (p<0.001). Age, gender, and pain experience were important variables that affected patients' fear of injections. With a one-unit increase in age, the injection fear score decreased by 0.13 points, and the mean injection fear score of women was 2.11 points higher than that of men. It was determined that the patient's age, gender, living with whom, and blood donation history were important variables affecting the fear of self-testing. It is seen that the fear test score decreases by 0.18 points with an increase in age by one unit, and the fear test scores of women compared to men are on average 3,358 points, the fear test scores of those living alone are 4,711 points compared to those living with family members, and the fear test scores of those who do not donate blood are 2,572 compared to those who donate blood score, it was determined that those with more pain experience were 3,156 points higher on average than those with less fear of injection. As a result, it was seen that the most important factors affecting the fear of insulin injection and finger punching in individuals with diabetes were age, gender, pain experience, living with whom, and blood donation history.

Keywords: diabetes, needle phobia, fear of injection, insulin injection

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Authors: Tareq Hamadneh, Jochen Merker, Hassan Al-Zoubi

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Bernstein's expansion for exponentials in Taylor functions provides lower and upper optimization values for the range of its original function. these values converge to the original functions if the degree is elevated or the domain subdivided. Taylor polynomial can be applied so that the exponential is a polynomial of finite degree over a given domain. Bernstein's basis has two main properties: its sum equals 1, and positive for all x 2 (0; 1). In this work, we prove the existence of fixed points for exponential functions in a given domain using the optimization values of Bernstein. The Bernstein basis of finite degree T over a domain D is defined non-negatively. Any polynomial p of degree t can be expanded into the Bernstein form of maximum degree t ≤ T, where we only need to compute the coefficients of Bernstein in order to optimize the original polynomial. The main property is that p(x) is approximated by the minimum and maximum Bernstein coefficients (Bernstein bound). If the bound is contained in the given domain, then we say that p(x) has fixed points in the same domain.

Keywords: Bernstein polynomials, Stability of control functions, numerical optimization, Taylor function

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Authors: M. K. Witek-Hajduk, T. M. Napiórkowski

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A number of studies discussed the topic of benefits of retailers-manufacturers cooperation and coopetition. However, there are only few publications focused on the benefits of cooperation and coopetition between retailers and their suppliers of durable consumer goods; especially in the context of business model of cooperating partners. This paper aims to provide a clustering approach to segment retailers selling consumer durables according to the benefits they obtain from their cooperation with key manufacturers and differentiate the said retailers’ in term of the business models of cooperating partners. For the purpose of the study, a survey (with a CATI method) collected data on 603 consumer durables retailers present on the Polish market. Retailers are clustered both, with hierarchical and non-hierarchical methods. Five distinctive groups of consumer durables’ retailers are (based on the studied benefits) identified using the two-stage clustering approach. The clusters are then characterized with a set of exogenous variables, key of which are business models employed by the retailer and its partnering key manufacturer. The paper finds that the a combination of a medium sized retailer classified as an Integrator with a chiefly domestic capital and a manufacturer categorized as a Market Player will yield the highest benefits. On the other side of the spectrum is medium sized Distributor retailer with solely domestic capital – in this case, the business model of the cooperating manufactrer appears to be irreleveant. This paper is the one of the first empirical study using cluster analysis on primary data that defines the types of cooperation between consumer durables’ retailers and manufacturers – their key suppliers. The analysis integrates a perspective of both retailers’ and manufacturers’ business models and matches them with individual and joint benefits.

Keywords: benefits of cooperation, business model, cluster analysis, retailer-manufacturer cooperation

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Authors: Dongyeob Han, Jungwon Huh, Quang Huy Tran, Choonghyun Kang

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Unmanned Aerial Vehicles (UAVs) have been used for surveillance, monitoring, inspection, and mapping. In this paper, we present a systematic approach for automatic registration of UAV images for monitoring facilities such as building, green house, and civil structures. The two-step process is applied; 1) an image matching technique based on SURF (Speeded up Robust Feature) and RANSAC (Random Sample Consensus), 2) bundle adjustment of multi-temporal images. Image matching to find corresponding points is one of the most important steps for the precise registration of multi-temporal images. We used the SURF algorithm to find a quick and effective matching points. RANSAC algorithm was used in the process of finding matching points between images and in the bundle adjustment process. Experimental results from UAV images showed that our approach has a good accuracy to be applied to the change detection of facility.

Keywords: building, image matching, temperature, unmanned aerial vehicle

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Authors: Yakubu Suleiman, S. A. Musa

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The research was conducted to determine the physical characteristics of banana fruits that influenced consumer preferences for the fruit in Northern Nigeria. Socio-economic characteristics of the respondents were also identified. Simple descriptive statistics and Hedonic prices model were used to analyze the data collected for socio-economic and consumer preference respectively with the aid of 1000 structured questionnaires. The result revealed the value of R2 to be 0.633, meaning that, 63.3% of the variation in the banana price was brought about by the explanatory variables included in the model and the variables are: colour, size, degree of ripeness, softness, surface blemish, cleanliness of the fruits, weight, length, and cluster size of fruits. However, the remaining 36.7% could be attributed to the error term or random disturbance in the model. It could also be seen from the calculated result that the intercept was 1886.5 and was statistically significant (P < 0.01), meaning that about N1886.5 worth of banana fruits could be bought by consumers without considering the variables of banana included in the model. Moreover, consumers showed that they have significant preference for colours, size, degree of ripeness, softness, weight, length and cluster size of banana fruits and they were tested to be significant at either P < 0.01, P < 0.05, and P < 0.1 . Moreover, the result also shows that consumers did not show significance preferences to surface blemish, cleanliness and variety of the banana fruit as all of them showed non-significance level with negative signs. Based on the findings of the research, it is hereby recommended that plant breeders and research institutes should concentrate on the production of banana fruits that have those physical characteristics that were found to be statistically significance like cluster size, degree of ripeness,’ softness, length, size, and skin colour.

Keywords: analysis, consumers, preference, variables

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Authors: Suvorov Vasyl, Filipchuk Viktor

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Developmental Dysplasia of the Hip (DDH) is a frequent pathology in pediatric orthopedist’s practice. Neglected or residual cases of DDH in walking patients are usually treated using pelvic osteotomies. Plastic changes take place in hinge points due to acetabulum reorientation during surgery. Classically described hinge points and a traditional division of pelvic osteotomies on reshaping and reorientation are currently debated. The purpose of this article was to evaluate biomechanical changes during the most commonly used pelvic osteotomies (Salter, Dega, Pemberton) for DDH treatment in pediatric patients. Methods: virtual pelvic models of 2- and 6-years old patients were created, material properties were assigned, pelvic osteotomies were simulated and biomechanical changes were evaluated using finite element analysis (FEA). Results: it was revealed that the patient's age has an impact on pelvic bones and cartilages density (in younger patients the pelvic elements are more pliable - p<0.05). Stress distribution after each of the abovementioned pelvic osteotomy was assessed in 2- and 6-years old patients’ pelvic models; hinge points were evaluated. The new term "restriction point" was introduced, which means a place where restriction of acetabular deformity correction occurs. Pelvic ligaments attachment points were mainly these restriction points. Conclusions: it was found out that there are no purely reshaping and reorientation pelvic osteotomies as previously believed; the pelvic ring acts as a unit in carrying out the applied load. Biomechanical overload of triradiate cartilage during Salter osteotomy in 2-years old patient and in 2- and 6-years old patients during Pemberton osteotomy was revealed; overload of the posterior cortical layer in the greater sciatic notch in 2-years old patient during Dega osteotomy was revealed. Level of Evidence – Level IV, prognostic.

Keywords: developmental dysplasia of the hip, pelvic osteotomy, finite element analysis, hinge point, biomechanics

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Authors: J. Munuzuri, L. Onieva, J. Guadix, P. Cortes

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The aeronautical sector represents the main source of industrial development in the South of the Iberian Peninsula, with the establishment of key players like Embraer in Alentejo or Airbus in Andalusia. Subsequently, the economic promotion policies implemented in both neighbouring regions seek to consolidate a trans-border aeronautical cluster to gain critical mass and seek synergies between companies and research centres. The first step of the proposed scheme entails the identification of common interests shared by companies, technological centres and university research groups in both regions. This involves determining the specific type of activities carried out at the different companies established in the two regions (ranging from OEMs to SMEs) and also building a catalogue of available infrastructures and skills on the side of research centres and universities. The results of this first step reveal potential one-to-one partnerships, and also highlight the aggregate strengths and needs of the two regions within the aeronautical sector, taking into account both the current scenario and its expected evolution. The second step of the scheme focuses on the particularly relevant companies identified in the first step, and consists of the completion of in-depth technological audits liable to suggest potential development actions or R&D projects in those companies, counting when possible on the capabilities shown by other members of the cluster. These technological audits follow a three-round process aimed at identifying specific needs, validating those identifications and suggesting possible actions to be taken. The final objective of this methodology is to enhance the economic activity in the aeronautical sector in both regions, always with an innovative perspective. The success of the scheme should be measured in terms of partnerships created, R&D projects initiated, and spin-off companies generated.

Keywords: aeronautical sector, technological audits, technology transfer, trans-border cluster

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Authors: Frodouard Minani

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Since last decade, wireless sensor networks (WSNs) have been used in many areas like health care, agriculture, defense, military, disaster hit areas and so on. Wireless Sensor Networks consist of a Base Station (BS) and more number of wireless sensors in order to monitor temperature, pressure, motion in different environment conditions. The key parameter that plays a major role in designing a protocol for Wireless Sensor Networks is energy efficiency which is a scarcest resource of sensor nodes and it determines the lifetime of sensor nodes. Maximizing sensor node’s lifetime is an important issue in the design of applications and protocols for Wireless Sensor Networks. Clustering sensor nodes mechanism is an effective topology control approach for helping to achieve the goal of this research. In this paper, the researcher presents an energy efficiency protocol to prolong the network lifetime based on Energy efficient clustering algorithm. The Low Energy Adaptive Clustering Hierarchy (LEACH) is a routing protocol for clusters which is used to lower the energy consumption and also to improve the lifetime of the Wireless Sensor Networks. Maximizing energy dissipation and network lifetime are important matters in the design of applications and protocols for wireless sensor networks. Proposed system is to maximize the lifetime of the Wireless Sensor Networks by choosing the farthest cluster head (CH) instead of the closest CH and forming the cluster by considering the following parameter metrics such as Node’s density, residual-energy and distance between clusters (inter-cluster distance). In this paper, comparisons between the proposed protocol and comparative protocols in different scenarios have been done and the simulation results showed that the proposed protocol performs well over other comparative protocols in various scenarios.

Keywords: base station, clustering algorithm, energy efficient, sensors, wireless sensor networks

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Authors: Ali Mohammadi

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The basis for the construction of any project is a map, a map where the surveyor can determine the coordinates of the points on the ground by using the coordinates and using the total station, projects such as dams, roads, tunnels and pipelines, if the base points are determined using GPS prepared can create challenges for the surveyor to control. First, we will examine some map projection on which the maps are designed, and a summary of their differences and the challenges that surveyors face in order to control them, because in order to build projects, we need real lengths and angles, so we have to use coordinates that provide us with the results of the calculations. We will examine some examples to understand the concept of localization so that the surveyor knows if he is facing a challenge or not and if he is faced with this challenge, how should he solve this problem.

Keywords: UTM, scale factor, cartesian, traverse

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Authors: D. S. Palimkar

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Random fixed point theory has received much attention in recent years, and it is needed for the study of various classes of random equations. The study of random fixed point theorems was initiated by the Prague school of probabilistic in the 1950s. The existence and uniqueness of fixed points for the self-maps of a metric space by altering distances between the points with the use of a control function is an interesting aspect in the classical fixed point theory. In a new category of fixed point problems for a single self-map with the help of a control function that alters the distance between two points in a metric space which they called an altering distance function. In this paper, we prove the results of existence of random common fixed point and its uniqueness for a pair of random mappings under weakly contractive condition for generalizing alter distance function in polish spaces using Random Common Fixed Point Theorem for Generalized Weakly Contractions.

Keywords: Polish space, random common fixed point theorem, weakly contractive mapping, altering function

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Authors: Xiaoxiao Li, Shuangcheng Jia, Qian Li

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Keypoint detection has always been a challenge in the field of image recognition. This paper proposes a novelty keypoint detection method which is called Multi-Scale Feature Fusion Convolutional Network with Attention (MFFCNA). We verified that the multi-scale features with the attention mechanism module have better feature expression capability. The feature fusion between different scales makes the information that the network model can express more abundant, and the network is easier to converge. On our self-made street sign corner dataset, we validate the MFFCNA model with an accuracy of 97.8% and a recall of 81%, which are 5 and 8 percentage points higher than the HRNet network, respectively. On the COCO dataset, the AP is 71.9%, and the AR is 75.3%, which are 3 points and 2 points higher than HRNet, respectively. Extensive experiments show that our method has a remarkable improvement in the keypoint recognition tasks, and the recognition effect is better than the existing methods. Moreover, our method can be applied not only to keypoint detection but also to image classification and semantic segmentation with good generality.

Keywords: keypoint detection, feature fusion, attention, semantic segmentation

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Authors: Yasuyuki Takahashi, Maya Yamashita, Kyoko Saito

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In general, dynamic SPECT data acquisition needs a few minutes for one rotation. Thus, the time-activity curve (TAC) derived from the dynamic SPECT is relatively coarse. In order to effectively shorten the interval, between data points, we adopted a 180-degree interpolation method. This method is already used for reconstruction of the X-ray CT data. In this study, we applied this 180-degree interpolation method to SPECT and investigated its effectiveness.To briefly describe the 180-degree interpolation method: the 180-degree data in the second half of one rotation are combined with the 180-degree data in the first half of the next rotation to generate a 360-degree data set appropriate for the time halfway between the first and second rotations. In both a phantom and a patient study, the data points from the interpolated images fell in good agreement with the data points tracking the accumulation of 99mTc activity over time for appropriate region of interest. We conclude that data derived from interpolated images improves the apparent time resolution of dynamic SPECT.

Keywords: dynamic SPECT, time resolution, 180-degree interpolation method, 99mTc-GSA.

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Authors: Arzu Baloglu, Ugur Kaplancali

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This paper focuses on Background Check Systems and Pre-Employment Screening. In our study, we attempted to make an online background checking site that will help employers when hiring employees. Our site has two types of users which are free and powered user. Free users are the employees and powered users are the employers which will hire employers. The database of the site will contain all the information about the employees and employers which are registered in the system so the employers can make a search based on their searching criteria to find the suitable employee for the job. The web site also has a comments and points system. The current employer can make comments to his/her employees and can also give them points. The comments will be shown on employee’s profile, so; when an employer searches for an employee he/she can check the points and comments of the employee to see whether he or she is capable of the job or not. The employers can also follow some employees if they desire. This paper has been designed and implemented with using ASP.NET, C# and JavaScript. The outputs have a user friendly interface. The interface also aimed to provide the useful information for Turkish Technology Companies.

Keywords: background, checking, verification, human resources, online

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Authors: Lidija Jevrić, Denis Kučević, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Milica Karadžić

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In the present study, the Hierarchical Cluster Analysis (HCA) was applied in order to determine the differences between the milk samples originating from a conventional dairy farm (CF) and an organic dairy farm (OF) in AP Vojvodina, Republic of Serbia. The clustering was based on the basis of the average values of saturated fatty acids (SFA) content and unsaturated fatty acids (UFA) content obtained for every season. Therefore, the HCA included the annual SFA and UFA content values. The clustering procedure was carried out on the basis of Euclidean distances and Single linkage algorithm. The obtained dendrograms indicated that the clustering of UFA in OF was much more uniform compared to clustering of UFA in CF. In OF, spring stands out from the other months of the year. The same case can be noticed for CF, where winter is separated from the other months. The results could be expected because the composition of fatty acids content is greatly influenced by the season and nutrition of dairy cows during the year.

Keywords: chemometrics, clustering, food engineering, milk quality

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Authors: Amro Matyori, Fatimah Sherbeny, Askal Ali, Olayiwola Popoola

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Objectives: The study evaluated the impact of COVID-19 on anxiety levels in the general population in the United States. Methods: The study used an online questionnaire. It adopted the Generalized Anxiety Disorder Assessment (GAD-7) instrument. It is a self-administered scale with seven items used as a screening tool and severity measure for generalized anxiety disorder. The participants rated the frequency of anxiety symptoms in the last two weeks on a Likert scale, which ranges from 0-3. Then the item points are summed to provide the total score. Results: Thirty-two participants completed the questionnaire. Among them, 24 (83%) females and 5 (17%) males. The age range of 18-24-year-old represented the most respondents. Only one of the participants tested positive for the COVID-19, and 39% of them, one of their family members, friends, or colleagues, tested positive for the coronavirus. Moreover, 10% have lost a family member, a close friend, or a colleague because of COVID-19. Among the respondents, there were ten who scored approximately five points on the GAD-7 scale, which indicates mild anxiety. Furthermore, eight participants scored 10 to 14 points, which put them under the category of moderate anxiety, and one individual who was categorized under severe anxiety scored 15 points. Conclusions: It is identified that most of the respondents scored the points that put them under the mild anxiety category during the COVID-19 pandemic. It is also noticed that severe anxiety was the lowest among the participants, and people who tested positive and/or their family members, close friends, and colleagues were more likely to experience anxiety. Additionally, participants who lost friends or family members were also at high risk of anxiety. It is obvious the COVID-19 outcomes and too much thinking about the pandemic put people under stress which led to anxiety. Therefore, continuous assessment and monitoring of psychological outcomes during pandemics will help to establish early well-informed interventions.

Keywords: anxiety and covid-19, covid-19 and mental health outcomes, influence of covid-19 on anxiety, population and covid-19 impact on mental health

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Authors: B. Sayaheen

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The translator’s competence is one of the topics that has received a great deal of research in the field of translation studies because such competencies are still debatable and not yet agreed upon. Besides, scholars tackle this topic from different points of view. Approaches to teaching these competencies have gone through some developments. This paper aims at investigating these developments, exploring the major turning points and shifts in the developments of teaching methods in translator training. The significance of these turning points and the external or internal causes will also be discussed. Based on the past and present status of teaching approaches in translator training, this paper tries to predict the future of these approaches. This paper is mainly concerned with developments of teaching approaches in the West since the 1980s to the present. The reason behind choosing this specific period is not because translator training started in the 1980s but because most criticism of the teacher-centered approach started at that time. The implications of this research stem from the fact that it identifies the turning points and the causes that led teachers to adopt student-centered approaches rather than teacher-centered approaches and then to incorporate technology and the Internet in translator training. These reasons were classified as external or internal reasons. Translation programs in the West and in other cultures can benefit from this study. Translation programs in the West can notice that teaching translation is geared toward incorporating more technologies. If these programs already use technology and the Internet to teach translation, they might benefit from the assumed future direction of teaching translation. On the other hand, some non-Western countries, and to be specific some professors, are still applying the teacher-centered approach. Moreover, these programs should include technology and the Internet in their teaching approaches to meet the drastic changes in the translation process, which seems to rely more on software and technologies to accomplish the translator’s tasks. Finally, translator training has borrowed many of its approaches from other disciplines, mainly language teaching. The teaching approaches in translator training have gone through some developments, from teacher-centered to student-centered and then toward the integration of technologies and the Internet. Both internal and external causes have played a crucial role in these developments. These borrowed approaches should be comprehensively evaluated in order to see if they achieve the goals of translator training. Such evaluation may lead us to come up with new teaching approaches developed specifically for translator training. While considering these methods and designing new approaches, we need to keep an eye on the future needs of the market.

Keywords: turning points, developments, translator training, market, The West

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Authors: Jianghao Hu, Hongyu Wang

Abstract:

The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

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Authors: Jainendra Singh, Zaheeruddin

Abstract:

A typical wireless sensor networks (WSNs) consists of several tiny and low-power sensors which use radio frequency to perform distributed sensing tasks. The longevity of wireless sensor networks (WSNs) is a major issue that impacts the application of such networks. While routing protocols are striving to save energy by acting on sensor nodes, recent studies show that network lifetime can be enhanced by further involving sink mobility. A common approach for energy efficiency is partitioning the network into clusters with correlated data, where the representative nodes simply transmit or average measurements inside the cluster. In this paper, we propose an energy- efficient homogenous clustering (EHC) technique. In this technique, the decision of each sensor is based on their residual energy and an estimate of how many of its neighboring cluster heads (CHs) will benefit from it being a CH. We, also explore the routing algorithm in clustered WSNs. We show that the proposed schemes significantly outperform current approaches in terms of packet delay, hop count and energy consumption of WSNs.

Keywords: wireless sensor network, energy efficiency, clustering, routing

Procedia PDF Downloads 241

Authors: Kang-Mo Jung

Abstract:

The use of regularization for statistical methods has become popular. The least absolute shrinkage and selection operator (LASSO) framework has become the standard tool for sparse regression. However, it is well known that the LASSO is sensitive to outliers or leverage points. We consider a new robust estimation which is composed of the weighted loss function of the pairwise difference of residuals and the adaptive penalty function regulating the tuning parameter for each variable. Rank regression is resistant to regression outliers, but not to leverage points. By adopting a weighted loss function, the proposed method is robust to leverage points of the predictor variable. Furthermore, the adaptive penalty function gives us good statistical properties in variable selection such as oracle property and consistency. We develop an efficient algorithm to compute the proposed estimator using basic functions in program R. We used an optimal tuning parameter based on the Bayesian information criterion (BIC). Numerical simulation shows that the proposed estimator is effective for analyzing real data set and contaminated data.

Keywords: adaptive penalty function, robust penalized regression, variable selection, weighted rank regression

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Authors: Natalia Rudeli, Elisabeth Viles, Adrian Santilli

Abstract:

Delays in the construction industry are a global phenomenon. Many construction projects experience extensive delays exceeding the initially estimated completion time. The main purpose of this study is to identify construction projects typical behaviors in order to develop a prognosis and management tool. Being able to know a construction projects schedule tendency will enable evidence-based decision-making to allow resolutions to be made before delays occur. This study presents an innovative approach that uses Cluster Analysis Method to support predictions during Earned Value Analyses. A clustering analysis was used to predict future scheduling, Earned Value Management (EVM), and Earned Schedule (ES) principal Indexes behaviors in construction projects. The analysis was made using a database with 90 different construction projects. It was validated with additional data extracted from literature and with another 15 contrasting projects. For all projects, planned and executed schedules were collected and the EVM and ES principal indexes were calculated. A complete linkage classification method was used. In this way, the cluster analysis made considers that the distance (or similarity) between two clusters must be measured by its most disparate elements, i.e. that the distance is given by the maximum span among its components. Finally, through the use of EVM and ES Indexes and Tukey and Fisher Pairwise Comparisons, the statistical dissimilarity was verified and four clusters were obtained. It can be said that construction projects show an average delay of 35% of its planned completion time. Furthermore, four typical behaviors were found and for each of the obtained clusters, the interim milestones and the necessary rhythms of construction were identified. In general, detected typical behaviors are: (1) Projects that perform a 5% of work advance in the first two tenths and maintain a constant rhythm until completion (greater than 10% for each remaining tenth), being able to finish on the initially estimated time. (2) Projects that start with an adequate construction rate but suffer minor delays culminating with a total delay of almost 27% of the planned time. (3) Projects which start with a performance below the planned rate and end up with an average delay of 64%, and (4) projects that begin with a poor performance, suffer great delays and end up with an average delay of a 120% of the planned completion time. The obtained clusters compose a tool to identify the behavior of new construction projects by comparing their current work performance to the validated database, thus allowing the correction of initial estimations towards more accurate completion schedules.

Keywords: cluster analysis, construction management, earned value, schedule

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Authors: Rouighi Mustapha, Bouzid Laghaa Souad, Rouighi Tahar

Abstract:

Due to rain Shortage and the increase of population in the last years, wells excavation and groundwater use for different purposes had been increased without any planning. This is a great challenge for our country. Moreover, this scarcity of water resources in this region is unfortunately combined with rapid fresh water resources quality deterioration, due to salinity and contamination processes. Therefore, it is necessary to conduct the studies about groundwater quality in Algeria. In this work consists in the identification of the factors which influence the water quality parameters in Laghouat region by using statistical analysis Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and geographic information system (GIS) in an attempt to discriminate the sources of the variation of water quality variations. The results of PCA technique indicate that variables responsible for water quality composition are mainly related to soluble salts variables; natural processes and the nature of the rock which modifies significantly the water chemistry. Inferred from the positive correlation between K+ and NO3-, NO3- is believed to be human induced rather than naturally originated. In this study, the multivariate statistical analysis and GIS allows the hydrogeologist to have supplementary tools in the characterization and evaluating of aquifers.

Keywords: cluster, analysis, GIS, groundwater, laghouat, quality

Procedia PDF Downloads 300