Search results for: root shoot traits

Authors: Abdulkadir Abu Lawal

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For the dearth of reliable cardinal numerical data, the linked phenomena in productivity indices such as operational costs and company turnovers, etc. could not be investigated. This would not give us insight to the root of productivity problems at unique sites. So, ordinal ranking by professionals who were most directly involved with construction sites was applied for Kendall’s concordance. Responses gathered from independent architects, builders/engineers, and quantity surveyors were herein analyzed. They were responses based on factors that affect sites productivity, and these factors were categorized as head office factors, resource management effectiveness factors, motivational factors, and training/skill development factors. It was found that productivity is low and has to be improved in order to facilitate Nigerian efforts in bridging its infrastructure deficit. The significance of this work is underlined with the Kendall’s coefficient of concordance of 0.78, while remedial measures must be emphasized to stimulate better productivity. Further detailed study can be undertaken by using Fuzzy logic analysis on wider Delphi survey.

Keywords: factors, Kendall's coefficient of concordance, magnitude of agreement, percentage magnitude of dichotomy, ranking variables

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Authors: Shila Khayambashi

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For the past few decades, Western researchers studied different youth issues, such as bullying, peer-aggression, depression, self-harm, and suicide, in a formulated and standardized manner. These researchers have grounded their studies upon a series of introduced characteristics and traits, which pragmatically defined the action of the individuals involved in these activities (Olweus, 1994). The phenomena of bullying and peer-aggression have touched the lives of many immigrant youths, as well. However, in the case of these immigrant young adults, the Police investigated, and later dismissed, the victims’ involvement in drugs and gangs’ activities, instead of questioning the possibility of the peer-aggression. This paper argues that neither government officials nor school personnel has ever investigated any cyber-documentation which would clarify these youth’s untimely deaths or search for any indication of peer-aggression at school. Through my ongoing research, I will problematize the Eurocentric definition of bullying and its limitations. I question the assumed universality of these definitions’ characteristics and their lack of minority representation. This research questions explicitly the positionality of the displaced youth within the promised multiculturality of Canada. I will ask: Does one size fit all, considering the bio-psycho-socio-economic differences between the Eastern and the Western worlds? More importantly, how does the epidemy of the communicative devices, like smartphones, and communicative apps, like Twitter and Snapchats, facilitate or hinder peer-aggression for the displaced youths?

Keywords: Bullying , Immigrant youths, Peer aggression, Minority population

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Authors: Cosmas Nathanailides, Fotini Kakali, Kostas Karipoglou

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The filleting yield and the chemical composition of farmed sea bass (Dicentrarchus labrax); rainbow trout (Oncorynchus mykiss) and meagre (Argyrosomus regius) was investigated in farmed fish in NW Greece. The results provide an estimate of the quantity of fish required to produce one kilogram of fillet weight, an estimation which is required for the operational management of fish processing companies. Furthermore in this work, the ratio of feed input required to produce one kilogram of fish fillet (FFCR) is presented for the first time as a useful indicator of the ecological footprint of consuming farmed fish. The lowest lipid content appeared in meagre (1,7%) and the highest in trout (4,91%). The lowest fillet yield and fillet yield feed conversion ratio (FYFCR) was in meagre (FY=42,17%, FFCR=2,48), the best fillet yield (FY=53,8%) and FYFCR (2,10) was exhibited in farmed rainbow trout. This research has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: ARCHIMEDES III. Investing in knowledge society through the European Social Fund.

Keywords: farmed fish, flesh quality, filleting yield, lipid

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Authors: A. Nabhan, Mohamed R. El-Sharkawy, A. Rashed

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The main aim of this paper is to dedicate the belt drive system faults like cogs missing, misalignment and belt worm using vibration analysis technique. Experimentally, the belt drive test-rig is equipped to measure vibrations signals under different operating conditions. Finite element 3D model of belt drive system is created and vibration response analyzed using commercial finite element software ABAQUS/CAE.  Root mean square (RMS) and Crest Factor will serve as indicators of average amplitude of envelope analysis signals. The vibration signals pattern obtained from the simulation model and experimental data have the same characteristics. It can be concluded that each case of the RMS is more effective in detecting the defect for acceleration response. While Crest Factor parameter has a response with the displacement and velocity of vibration signals. Also it can be noticed that the model has difficulty in completing the solution when the misalignment angle is higher than 1 degree.

Keywords: simulation model, misalignment, cogs missing, vibration analysis

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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: Apolinar Picado, Ronald Solís, Rafael Gamero

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The thin-layer drying characteristics of instant coffee solution were investigated in a laboratory tunnel dryer. Drying experiments were carried out at three temperatures (80, 100 and 120 °C) and an air velocity of 1.2 m/s. Drying experimental data obtained are fitted to six (6) thin-layer drying models using the non-linear least squares regression analysis. The acceptability of the thin-layer drying model has been based on a value of the correlation coefficient that should be close to one, and low values for root mean square error (RMSE) and chi-square (x²). According to this evaluation, the most suitable model for describing drying process of thin-layer instant coffee solution is the Page model. Further, the effective moisture diffusivity and the activation energy were computed employing the drying experimental data. The effective moisture diffusivity values varied from 1.6133 × 10⁻⁹ to 1.6224 × 10⁻⁹ m²/s over the temperature range studied and the activation energy was estimated to be 162.62 J/mol.

Keywords: activation energy, diffusivity, instant coffee, thin-layer models

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Authors: A. Ejah Umraeni Salam, M. Tola, M. Selintung, F. Maricar

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Clean water is an essential and fundamental human need. Therefore, its supply must be assured by maintaining the quality, quantity and water pressure. However the fact is, on its distribution system, leakage happens and becomes a common world issue. One of the technical causes of the leakage is a leaking pipe. The purpose of the research is how to use the Radial Basis Function Neural (RBFNN) model to detect the location and the magnitude of the pipeline leakage rapidly and efficiently. In this study the RBFNN are trained and tested on data from EPANET hydraulic modeling system. Method of Radial Basis Function Neural Network is proved capable to detect location and magnitude of pipeline leakage with of the accuracy of the prediction results based on the value of RMSE (Root Meant Square Error), comparison prediction and actual measurement approaches 0.000049 for the whole pipeline system.

Keywords: radial basis function neural network, leakage pipeline, EPANET, RMSE

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Authors: Jasmine H. Gagnon

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The present study examined how grandiose narcissists make adaptive trade-offs between mating investment, parenting investment, and somatic investment relative to individuals without narcissistic personalities. A sample of 509 males and females between the ages of 24 and 35 years old (49.31% female) completed a personality inventory assessing Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness to Experience. In a Latent Profile Analysis (LPA), personality inventory scores were used to classify participants into latent groups. The model of best fit identified one grandiose narcissist group and three groups with non-narcissistic personalities. Covariate analyses revealed that individuals with narcissistic traits made significantly more significant somatic investments in comparison to two of the three non-narcissistic latent groups. No other significant differences between the narcissistic and non-pathological groups were found. Thus, grandiose narcissists trade off parenting and mating investments to make more significant somatic investments. That is, they expend a larger portion of their energetic resources on maintaining their physical health and careers and similar quantities of energetic resources on maintaining relationships with their offspring and potential romantic partners as individuals without narcissistic personalities.

Keywords: narcissism, grandiose narcissism, HEXACO, trade-offs, mating, parenting, somatic, dark triad

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Authors: Raphael Naryongo, Philip Ngare, Anthony Waititu

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This paper deals with numerical simulation of Wishart processes for a single asset risky pricing model whose volatility is described by Wishart affine diffusion processes. The multi-factor specification of volatility will make the model more flexible enough to fit the stock market data for short or long maturities for better returns. The Wishart process is a stochastic process which is a positive semi-definite matrix-valued generalization of the square root process. The aim of the study is to model the log asset stock returns under the double Wishart stochastic volatility model. The solution of the log-asset return dynamics for Bi-Wishart processes will be obtained through Euler-Maruyama discretization schemes. The numerical results on the asset returns are compared to the existing models returns such as Heston stochastic volatility model and double Heston stochastic volatility model

Keywords: euler schemes, log-asset return, infinitesimal generator, wishart diffusion affine processes

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Authors: Ranjana Dani

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Brand communication narratives in India has evolved today to reflect the vibrant and intriguing tone of voice inspired by a rich cultural heritage while addressing the culturally alert attitude of the contemporary global Indian. Brands are strongly associated with the organization's values, vision, and mission and portray this through specific ‘look and feel’ and ‘tone of voice’. It is within the brand’s visual language that COLOUR has evolved to become a most powerful weapon in the designer’s arsenal. Color is big business in Brand Design! A brand is a ‘collection of perceptions’, meaningful brand connect is about striving to occupy head and heart space in consumers. The persona of the young Indian reflects a deep attachment to cultural roots as seen through the characteristic of ‘Indie Pride,’ blended with the ambitious, aspirational traits of a modern ‘global citizen’.Studies on ‘Color Perceptions’ indicate a trend that amplifies this, and hence brands reflect a GLOCAL palette, a Global and Local Blend. This paper establishes this through case studies that expand the inspirations, selection processes, and use of innovative color palettes crafted by some dynamic brand designers. This throws light on the role of color as it generates visual impact and recall for successful brands.

Keywords: colour palettes, brand design and business, cultural context, colour perceptions, glocal, contemporaneity

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Authors: Senthilkumar S, Vijayakumar R M , Soorianathasundaram K, Durga Devi D

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A study was conducted to assess the influence of brassinosteroid and other bioregulators as pre-harvest sprays on yield and quality of newly introduced Californian grape cv. Italia. The vines were exposed to standardized pruning level of pruning 50% of the canes to 5-6 bud level for fruiting and 50% of the canes to two bud level for vegetative growth. The influence of brassinosteroid was assessed using BR (1 ppm) alone and in combination with GA3 and CPPU, sprayed at three different stages over the control (water spray) were given as treatments. The results revealed that the bunches treated with Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage i.e., 7-8 mm berry size, recorded the maximum values on yield characters like bunch weight (719.94 g), yield per vine (12.70 kg/vine) and yield per hectare (15.88 t). The berry characters and quality traits were also significantly influenced by the application of bioregulators. The maximum value for all those characters was registered under bunch sprays of Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage. The economic feasibility indicated that the treatment combination Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage (7-8 mm berry size) had registered the maximum benefit cost ratio of 3.13, as compared to 1.89 in control (water spray). Overall, it was observed that a combined bunch spray of Brassinosteroid (1 ppm) + GA3 (10 ppm) at pea stage (7-8 mm berry size) was adjudged as the best treatment for promoting the crop for better the bunch quality and yield.

Keywords: bioregulators, brassinosteroid, CPPU, GA3, Italia grape cultivar

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Authors: Eser Bingül

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The leadership and leaders, also having been a privileged subject of scientific researches in the last century, have become influential in shaping the destiny of the states since the first examples of the warfare history. The issue of leadership, finding a place in the management science, can also be defined as an integration of function within the aspect of leader. In this description, the relationship has come to the foreground which is established between the development of leadership theories and the elements of function which are leader, followers, and condition. While one reason of this analysis in leadership is to keep a lens to the historical background, the main reason has been a questioning the traits and education of leaders who have still affected the nation’s and organization’s fate. The links and analysis established in the definition of leadership have put forward the necessity of solving the unpredictable structure of human nature and behaviors in the focus of leadership approach. On the other hand becoming a model that meets the today’s needs of any system has given a clue that the leaders should turn towards the people. Being aware of this necessity, human-oriented leadership approach aims to gain both followers and their abilities to the system with giving them a deserved esteem and create the team spirit based on mutual trust. Ultimately this approach, with the determined leadership qualities consisting of charisma, ability of communication and trust, will be able to produce the solutions to the instant and long-term problems and uncertainties, derived from the variables of function, for the sake of systems.

Keywords: human nature, leadership, human-oriented approach, social sciences and humanities

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Authors: Adewale I. Adeolu, Vivian U. Oleforuh-Okoleh, Sylvester N. Ibe

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Heritability and repeatability estimates are needed for the genetic evaluation of livestock populations and consequently for the purpose of upgrading or improvement. Pooled data on 604 progeny from three consecutive parities of purebred rabbit breeds (Chinchilla, Dutch and New Zealand white) raised in Derived Savanna Zone of Nigeria were used to estimate heritability and repeatability for pre-weaning body weights between 1st and 8th week of age. Traits studied include Individual kit weight at birth (IKWB), 2nd week (IK2W), 4th week (IK4W), 6th week (IK6W) and 8th week (IK8W). Nested random effects analysis of (Co)variances as described by Statistical Analysis System (SAS) were employed in the estimation. Respective heritability estimates from the sire component (h2s) and repeatability (R) as intra-class correlations of repeated measurements from the three parties for IKWB, IK2W, IK4W and IK8W are 0.59±0.24, 0.55±0.24, 0.93±0.31, 0.28±0.17, 0.64±0.26 and 0.12±0.14, 0.05±0.14, 0.58±0.02, 0.60±0.11, 0.20±0.14. Heritability and repeatability (except R for IKWB and IK2W) estimates are moderate to high. In conclusion, since pre-weaning body weights in the present study tended to be moderately to highly heritable and repeatable, improvement of rabbits raised in derived savanna zone can be realized through genetic selection criterions.

Keywords: heritability, nested design, parity, pooled data, repeatability

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Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar

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Several meteorological parameters were used for the prediction of monthly average daily global solar radiation on horizontal using recurrent neural networks (RNNs). Climatological data and measures, mainly air temperature, humidity, sunshine duration, and wind speed between 1995 and 2007 were used to design and validate a feed forward and recurrent neural network based prediction systems. In this paper we present our reference system based on a feed-forward multilayer perceptron (MLP) as well as the proposed approach based on an RNN model. The obtained results were promising and comparable to those obtained by other existing empirical and neural models. The experimental results showed the advantage of RNNs over simple MLPs when we deal with time series solar radiation predictions based on daily climatological data.

Keywords: recurrent neural networks, global solar radiation, multi-layer perceptron, gradient, root mean square error

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Authors: Sue Lynn Kim, Sang-Gyun Lee, Joan P. Yoo

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Although adolescents in low socioeconomic status (SES) have been reported to less engage in health promoting behaviors (HPB), the specific mechanism between their SES and HPB has not been extensively studied. Considering the Korean education system which focuses only on college entrance exams while lacking of interest in students’ health, and unique traits of adolescents, such as ego-centric thinking, family members can significantly contribute to develop and enhance adolescents’ HPB. Based on the review of related literature and previous researches, this study examined the mediating effect of family-based activities on the relationship between SES and adolescents' HPB. 636 adolescents (4th graders in elementary and 1st graders in middle school) and their parents from the 1st year survey of Seoul Education & Health Welfare Panel were analyzed by AMOS 19.0 utilizing structural equation modeling. Analytic results show that adolescents in low SES were less likely to engage in family-based activities as well as HPB. This association between SES and HPB was partially mediated by family-based activities. Based on the findings, we suggest that special education programs to enhance HPB should be required in schools and community organizations especially for adolescents in low SES who may have difficulties in doing family-based activities due to parents’ low income and insufficient leisure time. In addition, family-based activities should be encouraged to enhance HPB by raising parents' awareness about the importance of family-based activities on their children's HPB.

Keywords: family-based activity, health promoting behaviors, socioeconomic status, HPB

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Authors: Hyun-Woo Cho

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It is quite important to utilize right time and intelligent production monitoring and diagnosis of industrial processes in terms of quality and safety issues. When compared with monitoring task, fault diagnosis represents the task of finding process variables responsible causing a specific fault in the process. It can be helpful to process operators who should investigate and eliminate root causes more effectively and efficiently. This work focused on the active use of combining a nonlinear statistical technique with a preprocessing method in order to implement practical real-time fault identification schemes for data-rich cases. To compare its performance to existing identification schemes, a case study on a benchmark process was performed in several scenarios. The results showed that the proposed fault identification scheme produced more reliable diagnosis results than linear methods. In addition, the use of the filtering step improved the identification results for the complicated processes with massive data sets.

Keywords: diagnosis, filtering, nonlinear statistical techniques, process monitoring

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Authors: Andressa dos Santos Nicolau, João P. da S.C Algusto, Claudio Márcio do N. A. Pereira, Roberto Schirru

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In case of abnormal situations, the nuclear power plant (NPP) operators must follow written procedures to check the condition of the plant and to classify the type of emergency. In this paper, we proposed a Real Time Expert System in order to improve operator’s performance in case of transient or accident with reactor shutdown. The expert system’s knowledge is based on the sequence of events (SoE) of known accident and two emergency procedures of the Brazilian Pressurized Water Reactor (PWR) NPP and uses two kinds of knowledge representation: rule and logic trees. The results show that the system was able to classify the response of the automatic protection systems, as well as to evaluate the conditions of the plant, diagnosing the type of occurrence, recovery procedure to be followed, indicating the shutdown root cause, and classifying the emergency level.

Keywords: emergence procedure, expert system, operator support, PWR nuclear power plant

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Authors: Nguyen Cao Nguyen, Krasimir I. Ivanov, Penka S. Zapryanova

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The present study was carried out to investigate the interaction of foliar applied zinc with other elements in Phyllanthus amarus plants. The plant samples for our experiment were collected from Lam Dong province, Vietnam. Seven suspension solutions of nanosized zinc hydroxide nitrate (Zn₅(OH)₈(NO₃)₂·2H₂O) with different Zn concentration were used. Fertilization and irrigation were the same for all variants. The Zn content and the content of selected micro (Cu, Fe, Mn) and macro (Ca, Mg, P and K) nutrients in plant roots, and stems and leaves were determined. It was concluded that the zinc content of plant roots varies narrowly, with no significant impact of ZnHN fertilization. The same trend can be seen in the content of Cu, Mn, and macronutrients. The zinc content of plant stems and leaves varies within wide limits, with the significant impact of ZnHN fertilization. The trends in the content of Cu, Mn, and macronutrients are kept the same as in the root, whereas the iron trends to increase its content at increasing the zinc content.

Keywords: Phyllanthus amarus, Zinc, Micro and macro elements, foliar fertilizer

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Authors: Anil Kumar, Diwakar Aggarwal, M. Sudhakara Reddy

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The wood of Eucalyptus, Populus and bamboos are some important species used as raw material for the manufacture of pulp. However, higher levels of lignin pose a problem during Kraft pulping and yield of pulp is also lower. In order to increase the yield of pulp per unit wood and reduce the use of chemicals during kraft pulping it is important to reduce the lignin content and/or increase cellulose content in wood. Cellulose biosynthesis in wood takes place by the coordinated action of many enzymes. The two important enzymes are KORRIGAN and SUCROSE SYNTHASE. KORRIGAN (Endo-1,4--glucanase) is implicated in the process of editing growing cellulose chains and improvement of the crystallinity of produced cellulose, whereas SUCROSE SYNTHASE is involved in providing substrate (UDP-glucose) for growing cellulose chains. The present study was aimed at the cloning, characterization and overexpression of these genes in Eucalyptus and Populus. An efficient shoot organogenesis protocol from leaf explants taken from micro shoots of the species has been developed. Agrobacterium mediated genetic transformation using Agrobacterium tumefaciens strain EHA105 and LBA4404 harboring binary vector pBI121 was achieved. Both the genes were cloned from cDNA library of Populus deltoides. These were subsequently characterized using various bioinformatics tools. The cloned genes were then inserted into pBI121 under the CaMV35S promotors replacing GUS gene. The constructs were then mobilized into above strains of Agrobacterium and used for the transformation work. Subsequently, genetic transformation of these clones with target genes following already developed protocol is in progress. Four transgenic lines of Eucalyptus tereticornis overexpressing Korrigan gene under the strong constitutive promoters CaMV35S have been developed, which are being further evaluated. Work on development of more transgenic lines overexpressing these genes in Populus and Eucalyptus is also in progress. This presentation will focus on important developments in this direction.

Keywords: Eucalyptus tereticornis, genetic transformation, Kraft pulping Populus deltoides

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Authors: Syed Ali Shahbaz Shah

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In the last few years, Bituminous Asphaltic roads are becoming popular day by day in the world. Plenty of research has been carried out to identify many advantages like safety, environmental effects, and comfort. Some other benefits are minimal noise and skid resistance enhancement. Besides the benefits of asphaltic roads, the permeable structure of the road also causes some distress, and raveling is one of the crucial defects. The main reason behind this distress is the failure of adhesion between bitumen mortar, specifically due to excessive load from heavy traffic. The main focus of this study is to identify the root cause and propose both the long-term and the short-term solutions of raveling on a specific road section depicting the overall road situation from the bridge of Kahuta road towards the intersection of the Islamabad express highway. The methodology adopted for this purpose is visual inspections in-situ. It was noted that there were chunks of debris on the road surface, which indicates that the asphalt binder is aged the most probably. Further laboratory testing would confirm that either asphalt binder is aged or inadequate compaction was adept during cold weather paving.

Keywords: asphaltic roads, asphalt binder, distress, raveling

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Authors: Taegyoo Woo, Jong Kang Park, Jong Tae Kim

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Visible Light Communication (VLC) provides wireless communication features in illumination systems. One of the key applications is to recognize the user location by indoor illuminators such as light emitting diodes. For localization of individual receivers in these systems, we usually assume that receivers and transmitters are placed in parallel. However, it is difficult to satisfy this assumption because the receivers move randomly in real case. It is necessary to analyze the case when transmitter is not placed perfectly parallel to receiver. It is also important to identify changes on optical gain by the tilted angles and distances of them against the illuminators. In this paper, we simulate optical gain for various cases where the tilt of the receiver and the distance change. Then, we identified changing patterns of optical gains according to tilted angles of a receiver and distance. These results can help many VLC applications understand the extent of the location errors with regard to optical gains of the receivers and identify the root cause.

Keywords: visible light communication, incident angle, optical gain, light emitting diode

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Authors: Mohamed Fadzlee Sulaiman, Mohd Zabri Adil Talib, Aswami Fadillah Mohd Ariffin

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Each individual organization has their own mechanism to build up cyber defense capability in protecting their information infrastructures from data breaches and cyber espionage. But, we can not deny the possibility of failing to detect and stop cyber attacks especially for those targeting credential information and intellectual property (IP). In this paper, we would like to share the modern approach of effective digital forensic methodology in order to identify the artifacts in tracing the trails of evidence while mitigating the infection from the target machine/s. This proposed approach will suit the digital forensic investigation to be conducted while resuming the business critical operation after mitigating the infection and minimizing the risk from the identified attack to transpire. Therefore, traditional digital forensics methodology has to be improvised to be proactive which not only focusing to discover the root caused and the threat actor but to develop the relevant mitigation plan in order to prevent from the same attack.

Keywords: digital forensic, detection, eradication, targeted attack, malware

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Authors: Tin Thongthammachart, Wanida Jinsart

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Atmospheric particulate matter particles with a diameter less than 10 microns (PM₁₀) and less than 2.5 microns (PM₂.₅) have adverse health effect. The impact from PM was studied from both health and regulatory perspective. Ambient PM data was collected over ten years in Bangkok and vicinity areas of Thailand from 2007 to 2017. Statistical models were used to forecast PM concentrations from 2018 to 2020. Monitoring monthly data averaged concentration of PM₁₀ and PM₂.₅ were used as input to forecast the monthly average concentration of PM. The forecasting results were validated by root means square error (RMSE). The predicted results were used to determine hazard risk for the carcinogenic disease. The health risk values were interpolated with GIS with ordinary kriging technique to create hazard maps in Bangkok and vicinity area. GIS-based maps illustrated the variability of PM distribution and high-risk locations. These evaluated results could support national policy for the sake of human health.

Keywords: PM₁₀, PM₂.₅, statistical models, atmospheric particulate matter

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Authors: Azar Khodabakhshi, Elham Bolandnazar

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Agriculture as the most important food manufacturing sector is not only the energy consumer, but also is known as energy supplier. Using energy is considered as a helpful parameter for analyzing and evaluating the agricultural sustainability. In this study, the pattern of energy consumption of strawberry greenhouses of Jiroft in Kerman province of Iran was surveyed. The total input energy required in the strawberries production was calculated as 113314.71 MJ /ha. Electricity with 38.34% contribution of the total energy was considered as the most energy consumer in strawberry production. In this study, Neuro Fuzzy networks was used for function modeling in the production of strawberries. Results showed that the best model for predicting the strawberries function had a correlation coefficient, root mean square error (RMSE) and mean absolute percentage error (MAPE) equal to 0.9849, 0.0154 kg/ha and 0.11% respectively. Regards to these results, it can be said that Neuro Fuzzy method can be well predicted and modeled the strawberry crop function.

Keywords: crop yield, energy, neuro-fuzzy method, strawberry

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Authors: Silvia Rahmita

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Entrepreneurial success is crucial for economic growth, competitiveness, and job creation, yet many entrepreneurs face failure due to various challenges. This paper explores the critical role of strategic thinking in mitigating entrepreneurial failure. Entrepreneurial competencies—encompassing knowledge, skills, and traits—are essential for creating and growing ventures. Despite these competencies, numerous entrepreneurs fail due to poor management, inadequate support, and ineffective policies. The paper categorizes entrepreneurial failures into financial, operational, market, product or service, strategic, leadership, legal, human capital, technological, and environmental failures. Each failure type can be addressed through strategic thinking, which involves foresight, balancing short-term and long-term goals, and hypothesis-driven processes. By integrating strategic thinking into their approach, entrepreneurs can enhance risk management, adapt to market changes, and sustain growth. This process involves setting clear goals, innovating products, and maintaining a competitive edge. Ultimately, strategic thinking provides a framework for proactive planning, adaptation, and continuous improvement, reducing the likelihood of failure and ensuring long-term success. Entrepreneurs who prioritize strategic thinking are better equipped to navigate the complexities of the business environment and achieve sustainable growth.

Keywords: entrepreneurial failure, strategic thinking, risk management, business failure

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Authors: Jae-Hyung Jin, Kyung-Tae Lee, Yee-Seul So, Eunji Jeong, Yeonseon Lee, Dongpil Lee, Dong-Gi Lee, Yong-Sun Bahn

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Cryptococcus neoformans causes cryptococcal meningoencephalitis mainly in immunocompromised patients as well as immunocompetent people. But therapeutic options are limited to treat cryptococcosis. Some signaling pathways including cyclic AMP pathway, MAPK pathway, and calcineurin pathway play a central role in the regulation of the growth, differentiation, and virulence of C. neoformans. To understand signaling networks regulating the virulence of C. neoformans, we selected the 114 putative phosphatase genes, one of the major components of signaling networks, in the genome of C. neoformans. We identified putative phosphatases based on annotation in C. neoformans var. grubii genome database provided by the Broad Institute and National Center for Biotechnology Information (NCBI) and performed a BLAST search of phosphatases of Saccharomyces cerevisiae, Aspergillus nidulans, Candida albicans and Fusarium graminearum to Cryptococcus neoformans. We classified putative phosphatases into 14 groups based on InterPro phosphatase domain annotation. Here, we constructed 170 signature-tagged gene-deletion strains through homologous recombination methods for 91 putative phosphatases. We examined their phenotypic traits under 30 different in vitro conditions, including growth, differentiation, stress response, antifungal resistance and virulence-factor production.

Keywords: human fungal pathogen, phosphatase, deletion library, functional genomics

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Authors: Mehravar Javid

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This case study delves into the psychological complexities of a 33-year-old woman, the second of three children, whose upbringing under a critical mother and a high-expectation father has significantly shaped her psychological landscape. Exhibiting a blend of worthlessness and a grandiose self, her life is a constant struggle between idealizing her father and devaluing her mother and sisters, coupled with a fear of intimacy and a desire for merger. This internal conflict manifests in symptoms of depression, anxiety, and a pattern of forming and quitting multiple relationships, all driven by a deep-seated need for validation and approval. The therapeutic journey reveals her resistance to treatment, particularly when her defense mechanisms are challenged, reflecting a complex transference dynamic where she yearns for merger yet fears it. The treatment focuses on empathetically addressing her idealization and mirroring needs, allowing for autonomy while repairing communication gaps. This approach not only confronts her emotional deficits rooted in her family dynamics but also aids in her quest for self-identity, navigating through her feelings of emptiness, inferiority, and powerlessness. The study highlights the nuanced interplay of family influence on the development and maintenance of narcissistic traits, offering insights into the therapeutic strategies that can facilitate growth and self-awareness in similar cases.

Keywords: narcissistic personality disorder, merger transference, treatment interruption, case study, family dynamics

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Authors: Evelyn Smith, Susan Simpson

Abstract:

Background: Eating disorder (ED) treatment is complicated by high rates of chronicity, comorbidity, complex personality traits and client dropout. Given these complexities, Schema Therapy (ST) has been identified as a suitable treatment option. The study primarily aims to evaluate the efficacy of group ST for the treatment of EDs. The study further evaluated the effectiveness of ST in reducing schemas and improving quality of life. Method: Participant suitability was ascertained using the Eating Disorder Examination. Following this, participants attended 90-minute weekly group sessions over 25 weeks. Groups consisted of six to eight participants and were facilitated by two psychologists, at least one of who is trained in ST. Measures were completed at pre, mid and post-treatment. Measures assessed ED symptoms, cognitive schemas, schema mode presentations, quality of life, self-compassion and psychological distress. Results: As predicted, measures of ED symptoms were significantly reduced following treatment. No significant changes were observed in early maladaptive schema severity; however, reductions in schema modes were observed. Participants did not report improvements in general quality of life measures following treatment, though improvement in psychological well-being was observed. Discussion: Overall, the findings from the current study support the use of group ST for the treatment of EDs. It is expected that lengthier treatment is needed for the reduction in schema severity. Given participant dropout was considerably low, this has important treatment implications for the suitability of ST for the treatment of EDs.

Keywords: eating disorders, schema therapy, treatment, quality of life

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Authors: Xinyuan Y. Song, Kai Kang

Abstract:

Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

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Authors: Mohammed Al Sulaimani, Hamad Al Manhi

Abstract:

With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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