Search results for: applied behavior therapy

Authors: Sanjay Kumar Parjapati, Ajai Jain

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This paper presents optimization of makespan for ‘n’ jobs and ‘m’ machines flexible job shop scheduling problem with sequence dependent setup time using genetic algorithm (GA) approach. A restart scheme has also been applied to prevent the premature convergence. Two case studies are taken into consideration. Results are obtained by considering crossover probability (pc = 0.85) and mutation probability (pm = 0.15). Five simulation runs for each case study are taken and minimum value among them is taken as optimal makespan. Results indicate that optimal makespan can be achieved with more than one sequence of jobs in a production order.

Keywords: flexible job shop, genetic algorithm, makespan, sequence dependent setup times

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Authors: M. Adamski, J. Cwiklak

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The contemporary battlefield creates a demand for more costly and highly advanced munitions. Training personnel responsible for operations, as well as an immediate execution of combat tasks, which engage real assets, is unrealistic and economically not feasible. Owing to a wide array of exploited simulators and various types of imitators, it is possible to reduce the costs. One of the effective elements of training, which can be applied in the training of all service branches, are imitators of aerial targets. This research serves as an introduction to the commencement of design analysis over a real aerial target imitator. Within the project, the basic aerodynamic calculations were made, which enabled to determine its geometry, design layout, performance, as well as the mass balance of individual components. The conducted calculations of the parameters of flight characteristics come closer to the real performance of such unmanned aerial vehicles.

Keywords: aerial target, aerodynamics, imitator, performance

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Authors: Al Romano, Jeryl C. Hije, Mechaela Marie O. Tabiolo

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The decline in water quality is a major factor in aquatic disease outbreaks and can lead to significant mortality among aquatic organisms. Understanding the relationship between dissolved oxygen (DO) and water temperature is crucial, as these variables directly impact the health, behavior, and survival of fish populations. This study investigated how DO levels, water temperature, and atmospheric temperature interact in Sampaloc Lake to assess the risk of fish mortality. By employing a combination of linear regression models and machine learning techniques, researchers developed predictive models to forecast DO concentrations at various depths. The results indicate that while DO levels generally decrease with depth, the predicted concentrations are sufficient to support the survival of common fish species in Sampaloc Lake during March, April, and May 2025.

Keywords: aquaculture, dissolved oxygen, water temperature, regression analysis, machine learning, fish mass mortality, early warning system

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Authors: Ali Maksum

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In a number of countries, including Indonesia, the tendency for non-communicable diseases is increasing. As a result, health costs must be paid by the state continues to increase as well. People's lifestyles, including due to lack of physical activity, are thought to have contributed significantly to the problem. This study aims to examine the impact of participation in sports on quality of life, which is reflected in three main indicators, namely health, psychological, and social aspects. The study was conducted in the city of Surabaya and its surroundings, with a total of 490 participants, consisting of 245 men and 245 women with an average age of 45.4 years. Data on physical activity and quality of life were collected by questionnaire and analyzed using structural equation modeling. The test results of the model prove that the value of chi-square = 8,259 with p = .409, RMSEA = .008, NFI = .992, and CFI = 1. This means that the model is compatible with the data. The model explains that physical activity has a significant effect on quality of life. People who exercise regularly are better able to cope with stress, have a lower risk of illness, and have higher pro-social behavior. Therefore, it needs serious efforts from stakeholders, especially the government, to create an ecosystem that allows the growth of movement culture in the community.

Keywords: participation, physical activity, quality of life, structural equation modelling

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Authors: Davoud Beheshtizadeh, Farzin Malekpour

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The progress of technology and producing new machinery have made a big change in excavation operations and construction of underground structures. The limitations of space and some other economic, politic and military considerations gained the attention of most developed and developing countries towards the construction of these structures for mine, military, and development objectives. Underground highways, tunnels, subways, oil reservoir resources, fuels, nuclear wastes burying reservoir and underground stores are increasingly developing and being used in these countries. The existence and habitability of the cities depend on these underground installations or in other words these vital arteries. Stopping the flow of water, gas leakage and explosion, collapsing of sewage paths, etc., resulting from the earthquake are among the factors that can severely harm the environment and increase the casualty. Lack of sewage network and complete stoppage of the flow of water in Bam (Iran) is a good example of this kind. In this paper, we investigate the effect of wave orientation on structures and deformation of them and the effect of faulting on underground structures, and then, we study resistance of reinforced concrete against earthquake, simulate two different samples, analyze the result and point out the importance of paying attention to underground installations.

Keywords: underground structures, earthquake, underground installations, axial deformations

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Authors: Reem I. Altamimi, Geoff D. Skinner

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Extended periods engaged in sedentary behavior increases the risk of becoming overweight and/or obese which is linked to other health problems. Adding technology to the term ‘active living’ permits its inclusion in promoting and facilitating habitual physical activity. Technology can either act as a barrier to, or facilitate this lifestyle, depending on the chosen technology. Physical Activity Monitoring Technologies (PAMTs) are a popular example of such technologies. Different contemporary PAMTs have been evaluated based on customer reviews; however, there is a lack of published experimental research into the efficacy of PAMTs. This research aims to investigate the reliability of four PAMTs: two wristbands (Fitbit Flex and Jawbone UP), a waist-clip (Fitbit One), and a mobile application (iPhone Health Application) for recording a specific distance walked on a treadmill (1.5km) at constant speed. Physical activity tracking technologies are varied in their recordings, even while performing the same activity. This research demonstrates that Jawbone UP band recorded the most accurate distance compared to Fitbit One, Fitbit Flex, and iPhone Health Application.

Keywords: Fitbit, jawbone up, mobile tracking applications, physical activity tracking technologies

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Authors: Sara Zelman, Courtney Meyer, Hiren Patel, Lisa Philpotts, Sue Lahey, Thomas Burke

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Background: As the global burden of disease shifts from infectious diseases to noncommunicable diseases, there is growing urgency to provide treatment for time-sensitive illnesses, such as ST-Elevation Myocardial Infarctions (STEMIs). The standard of care for STEMIs in developed countries is Percutaneous Coronary Intervention (PCI). However, this is inaccessible in resource-limited settings. Before the discovery of PCI, Streptokinase (STK) and other thrombolytic drugs were first-line treatments for STEMIs. STK has been recognized as a cost-effective and safe treatment for STEMIs; however, in settings which lack access to PCI, it has not become the established second-line therapy. A systematic literature review was conducted to geographically map the use of STK for STEMIs in resource-limited settings. Methods: Our literature review group searched the databases Cinhal, Embase, Ovid, Pubmed, Web of Science, and WHO’s Index Medicus. The search terms included ‘thrombolytics’ AND ‘myocardial infarction’ AND ‘resource-limited’ and were restricted to human studies and papers written in English. A considerable number of studies came from Latin America; however, these studies were not written in English and were excluded. The initial search yielded 3,487 articles, which was reduced to 3,196 papers after titles were screened. Three medical professionals then screened abstracts, from which 291 articles were selected for full-text review and 94 papers were chosen for final inclusion. These articles were then analyzed and mapped geographically. Results: This systematic literature review revealed that STK has been used for the treatment of STEMIs in 33 resource-limited countries, with 18 of 94 studies taking place in India. Furthermore, 13 studies occurred in Pakistan, followed by Iran (6), Sri Lanka (5), Brazil (4), China (4), and South Africa (4). Conclusion: Our systematic review revealed that STK has been used for the treatment of STEMIs in 33 resource-limited countries, with the highest utilization occurring in India. This demonstrates that even though STK has high utility for STEMI treatment in resource-limited settings, it still has not become the standard of care. Future research should investigate the barriers preventing the establishment of STK use as second-line treatment after PCI.

Keywords: cardiovascular disease, global health, resource-limited setting, ST-Elevation Myocardial Infarction, Streptokinase

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Authors: Semyachkina-Glushkovskaya Oxana, Fedosov Ivan, Blokhina Inna, Terskov Andrey, Evsukova Arina, Elovenko Daria, Adushkina Viktoria, Dubrovsky Alexander, Jürgen Kurths

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In modern neurobiology, sleep is considered a novel biomarker and a promising therapeutic target for brain diseases. This is due to recent discoveries of the nighttime activation of the brain lymphatic system (BLS), playing an important role in the removal of wastes and toxins from the brain and contributes neuroprotection of the central nervous system (CNS). In our review, we discuss that night stimulation of BLS might be a breakthrough strategy in a new treatment of Alzheimer’s and Parkinson’s disease, stroke, brain trauma, and oncology. Although this research is in its infancy, however, there are pioneering and promising results suggesting that night transcranial photostimulation (tPBM) stimulates more effectively lymphatic removal of amyloid-beta from mouse brain than daily tPBM that is associated with a greater improvement of the neurological status and recognition memory of animals. In our previous study, we discovered that tPBM modulates the tone and permeability of the lymphatic endothelium by stimulating NO formation, promoting lymphatic clearance of wastes and toxins from the brain tissues. We also demonstrate that tPBM can also lead to angio- and lymphangiogenesis, which is another mechanism underlying tPBM-mediated stimulation of BLS. Thus, photo-augmentation of BLS might be a promising therapeutic target for preventing or delaying brain diseases associated with BLS dysfunction. Here we present pioneering technology for simultaneous tPBM in humans and sleep monitoring for stimulation of BLS to remove toxins from CNS and modulation of brain immunity. The wireless-controlled gadget includes a flexible organic light-emitting diode (LED) source that is controlled directly by a sleep-tracking device via a mobile application. The designed autonomous LED source is capable of providing the required therapeutic dose of light radiation at a certain region of the patient’s head without disturbing of sleeping patient. To minimize patients' discomfort, advanced materials like flexible organic LEDs were used. Acknowledgment: This study was supported by RSF project No. 23-75-30001.

Keywords: brain diseases, brain lymphatic system, phototherapy, sleep

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Authors: Jun Ming Moey, Zhiyaun Chen, David Nicholson

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Bad actors are often hard to detect in data that imprints their behaviour patterns because they are comparatively rare events embedded in non-bad actor data. An unsupervised machine learning framework is applied here to detect bad actors in financial crime datasets that record millions of transactions undertaken by hundreds of actors (<0.01% bad). Specifically, the framework combines ‘shallow’ (PCA, Isolation Forest) and ‘deep’ (Autoencoder) methods to detect outlier patterns. Detection performance analysis for both the individual methods and their combination is reported.

Keywords: detection, machine learning, deep learning, unsupervised, outlier analysis, data science, fraud, financial crime

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Authors: Yayun Hsu, Henry Horng-Shing Lu

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In this paper, a new method is proposed to extending the method of connected component labeling from processing binary images to multi-scale modeling of images. By using the adaptive threshold of multi-scale attributes, this approach minimizes the possibility of missing those important components with weak intensities. In addition, the computational cost of this approach remains similar to that of the typical approach of component labeling. Then, this methodology is applied to grain boundary detection and Drosophila Brain-bow neuron segmentation. These demonstrate the feasibility of the proposed approach in the analysis of challenging microscopy images for scientific discovery.

Keywords: microscopic image processing, scientific data mining, multi-scale modeling, data mining

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Authors: Žymantas Rudžionis, Paulius Grigaliūnas, Danutė Vaičiukynienė

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By planning this experimental work to investigate the effect of zeolitic waste on rheological and technological properties of self-compacting fiber reinforced concrete, we had an intention to draw attention to the environmental factor. Large amount of zeolitic waste, as a secondary raw materials are not in use properly and large amount of it is collected without a clear view of it’s usage in future. The principal aim of this work is to assure, that zeolitic waste admixture takes positive effect to the self-compacting fiber reinforced concrete mixes stability, flowability and other properties by using the experimental research methods. In addition to that a research on cement and zeolitic waste mortars were implemented to clarify the effect of zeolitic waste on properties of cement paste and stone. Primary studies indicates that zeolitic waste characterizes clear puzzolanic behavior, do not deteriorate and in some cases ensure positive rheological and mechanical characteristics of self-compacting concrete mixes.

Keywords: self compacting concrete, steel fiber reinforced concrete, zeolitic waste, rheological, properties of concrete, slump flow

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Authors: Khaled I. Nawafleh

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In this paper, it provide the canonical approach for studying dissipated oscillators based on the doubling of degrees of freedom. Clearly, expressions for Lagrangians of the elementary modes of the system are given, which ends with the familiar classical equations of motion for the dissipative oscillator. The equation for one variable is the time reversed of the motion of the second variable. it discuss in detail the extended Bateman Lagrangian specifically for a dual extended damped oscillator time-dependent. A Hamilton-Jacobi analysis showing the equivalence with the Lagrangian approach is also obtained. For that purpose, the techniques of separation of variables were applied, and the quantization process was achieved.

Keywords: doubling of degrees of freedom, dissipated harmonic oscillator, Hamilton-Jacobi, time-dependent lagrangians, quantization

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Authors: Tabassum Husain, Shen Peng Li, Zhaolin Chen

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This paper evaluates the usability of 3D Guided Image Filtering to enhance the quality of short-time binned dynamic PET images by using MRI images. Guided image filtering is an edge-preserving filter proposed to enhance 2D images. The 3D filter is applied on 1 and 5-minute binned images. The results are compared with 15-minute binned images and the Gaussian filtering. The guided image filter enhances the quality of dynamic PET images while also preserving important information of the voxels.

Keywords: dynamic PET images, guided image filter, image enhancement, information preservation filtering

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Authors: M. Benhaliliba, A. Ben Ahmed, C.E. Benouis, A.Ayeshamariam

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The properties of nonlinear optical NLOs are examined, and the results confirm the 2.19 eV HOMO-LUMO mismatch. In the Al-Pc cluster, certain functional bond lengths and bond angles have been observed. The Quantum chemical method (DFT and TD-DFT) and Vibrational spectra properties of AlPc are studied. X-ray pattern reveals the crystalline structure along with the (242) orientation of the AlPc organic thin layer. UV-Vis shows the frequency selective behavior of the device. The absorbance of such layer exhibits a high value within the UV range and two consecutive peaks within visible range. Spin coating is used to make an organic diode based on the Aluminium-phthalocynanine (AlPc-Cl) molecule. Under dark and light conditions, electrical characterization of Ag/AlPc/Si/Au is obtained. The diode's high rectifying capability (about 1x104) is subsequently discovered. While the height barrier is constant and saturation current is greatly reliant on light, the ideality factor of such a diode increases to 6.9 which confirms the non-ideality of such a device. The Cheung-Cheung technique is employed to further the investigation and gain additional data such as series resistance and barrier height.

Keywords: AlPc-Cl organic material, nonlinear optic, optical filter, diode

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Authors: Ran Etgar, Sarit Freund

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Agile project management (APM) has been developed originally for software development project. Construction projects seemed to be more apt to traditional water-fall approach than to APM. However, Construction project suffers from similar problems that necessitated the invention of APM, mainly the need to break down the project structure to small increments, thus minimizing the needed managerial planning and design. Since the classical structure of APM is not applicable the way it is to construction project, a modified version of APM was devised. This method, nicknamed 'The anchor method', exploits the fundamentals of APM (i.e., iterations, or sprints of short time frames or timeboxes, cross-functional teams, risk reduction and adaptation to changes) and adjust them to the construction world. The projects had to be structured appropriately to proactively and quickly adapt to change. The method aims to encompass human behavior and lean towards adaptivity rather than predictability. To enable smooth application of the method, a special project management software was developed, so as to provide solid administrational help and accurate data. The method is tested on a bunch of construction projects and some key performance indicators (KPIs) are collected. According to preliminary results the method is indeed very advantageous and with proper assimilation can radically change the construction project management paradigm.

Keywords: agile project management, construction, information systems, project management

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Authors: Shen Jian, Hu Jie, Zhu Guo Niu, Peng Ying Hong

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There are two issues exited in the traditional visual prosthesis: lacking systematic method and the low level of humanization. To tackcle those obstacles, a visual prosthesis design method based on biologically inspired design is proposed. Firstly, a constrained FBS knowledge cell model is applied to construct the functional model of visual prosthesis in biological field. Then the clustering results of engineering domain are ob-tained with the use of the cross-domain knowledge cell clustering algorithm. Finally, a prototype system is designed to support the bio-logically inspired design where the conflict is digested by TRIZ and other tools, and the validity of the method is verified by the solution scheme

Keywords: knowledge-based engineering, visual prosthesis, biologically inspired design, biomedical engineering

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Authors: Sawsan J. Al-Husseini, Talib A. Dosa

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Transformational leadership has been identified as the most important factor affecting innovation and knowledge sharing; it leads to increased goal-directed behavior exhibited by followers and thus to enhanced performance and innovation for the organization. However, there is a lack of models linking transformational leadership, knowledge sharing, and process innovation within higher education (HE) institutions in general within developing countries, particularly in Iraq. This research aims to examine the mediating role of knowledge sharing in the transformational leadership and process innovation relationship. A quantitative approach was taken and 254 usable questionnaires were collected from public HE institutions in Iraq. Structural equation modelling with AMOS 22 was used to analyze the causal relationships among factors. The research found that knowledge sharing plays a pivotal role in the relationship between transformational leadership and process innovation, and that transformational leadership would be ideal in an educational context, promoting knowledge sharing activities and influencing process innovation in the public HE in Iraq. The research has developed some guidelines for researchers as well as leaders and provided evidence to support the use of TL to increase process innovation within HE environment in developing countries, particularly in Iraq.

Keywords: transformational leadership, knowledge sharing, process innovation, structural equation modelling, developing countries

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Authors: Wan-Tzu Yen, Yu-Chen Luo, I-Ping Liu, Po-Hsuan Yeh, Sheng-Hsun Fu, Yuh-Lang Lee

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Self-assembled characteristics and adsorption performance of 1-dodecylamine molecules on gold (Au) (111) surfaces were characterized via cyclic voltammetry (CV), surface-enhanced infrared absorption spectroscopy (SEIRAS) and scanning tunneling microscopy (STM). The present study focused on the formation of 1-dodecylamine (DDA) on a gold surface with respect to the ex-situ arrangement of an adlayer on the Au(111) surface, and phase transition at potential dynamics carried out by EC-STM. This study reveals that alkyl amine molecules were formed an adsorption pattern with highly regular “lie down shape” on Au(111) surface, even in an extreme acid system (pH = 1). Acidic electrolyte (HClO₄) could protonate the surface of alkyl amine of a monolayer of the gold surface when potential shifts to negative. The quite stability of 1-dodecylamine on the gold surface maintained the monolayer across the potential window (0.1-0.8V). This transform model was confirmed by EC-STM. In addition, amine-modified Au(111) electrode adlayer used to examine how to affect an electron transfer across an interface using [Fe(CN)₆]³⁻/[Fe(CN)₆]⁴⁻ redox pair containing 0.1 M HClO₄ solution.

Keywords: cyclic voltammetry, dodecylamine, gold (Au)(111), scanning tunneling microscopy, self-assembled monolayer, surface-enhanced infrared absorption spectroscopy

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Authors: Teera Intararuang

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The purpose of this research is to study on the challenge and opportunity for waterway route management for promoting cultural tourism in Angsila District, Chonburi Province. To accomplish the goals and objectives, qualitative research will be applied. The research instruments used are observation, basic interviews, in-depth interviews, and interview key local performance. The study also uses both primary data and secondary data. From research result, it is revealed that all respondents had appreciated and strongly agree to promote their waterway route tourism as an intend for further increase for their income. However, it has some challenges to success this project due to natural obstacles such as water level, seasons and high temperature. Moreover, they lack financial support from government sectors also.

Keywords: Angsila community, waterway tourism route, cultural tourism, way of life

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Authors: Jadisha Cornejo, Helio Pedrini

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Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

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Authors: Shih-Pin Chen, Shih-Syuan You

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Fuzzy regression models are useful for investigating the relationship between explanatory variables and responses in fuzzy environments. To overcome the deficiencies of previous models and increase the explanatory power of fuzzy data, the graded mean integration (GMI) representation is applied to determine representative crisp regression coefficients. A fuzzy regression model is constructed based on the modified dissemblance index (MDI), which can precisely measure the actual total error. Compared with previous studies based on the proposed MDI and distance criterion, the results from commonly used test examples show that the proposed fuzzy linear regression model has higher explanatory power and forecasting accuracy.

Keywords: dissemblance index, fuzzy linear regression, graded mean integration, mathematical programming

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Authors: Mamadou I. Wade, Henry C. Ogworonjo, Madiha Gul, Mandoye Ndoye, Mohamed Chouikha, Wayne Patterson

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In this paper, we present a novel application of the Paillier cryptographic system to the encryption of RGB (Red Green Blue) images. In this method, an RGB image is first separated into its constituent channel images, and the Paillier encryption function is applied to each of the channels pixel intensity values. Next, the encrypted image is combined and compressed if necessary before being transmitted through an unsecured communication channel. The transmitted image is subsequently recovered by a decryption process. We performed a series of security and performance analyses to the recovered images in order to verify their robustness to security attack. The results show that the proposed image encryption scheme produces highly secured encrypted images.

Keywords: image encryption, Paillier cryptographic system, RBG image encryption, Paillier

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Authors: Feng Guo

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Human brain organoids, 3D brain tissue cultures derived from human pluripotent stem cells, hold promising potential in modeling neuroinflammation for a variety of neurological diseases. However, challenges remain in generating standardized human brain organoids that can recapitulate key physiological features of a human brain. Here, this study presents a series of organoids-on-a-chip systems to generate better human brain organoids and model neuroinflammation. By employing 3D printing and microfluidic 3D cell culture technologies, the study’s systems enable the reliable, scalable, and reproducible generation of human brain organoids. Compared with conventional protocols, this study’s method increased neural progenitor proliferation and reduced heterogeneity of human brain organoids. As a proof-of-concept application, the study applied this method to model substance use disorders.

Keywords: human brain organoids, microfluidics, organ-on-a-chip, neuroinflammation

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Authors: Rosana Marar, Edward Jaser

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This paper presents a software solution to enhance the content and presentation of graphic design and animation related textbooks. Using augmented and virtual reality concepts, a mobile application is developed to improve the static material found in books. This allows users to interact with animated examples and tutorials using their mobile phones and stereoscopic 3D viewers which will enhance information delivery. The application is tested on Google Cardboard with visual content in 3D space. Evaluation of the proposed application demonstrates that it improved the readability of static content and provided new experiences to the reader.

Keywords: animation, augmented reality, google cardboard, interactive media, technology enhanced learning, virtual reality

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Authors: Juha Kettunen

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The study analyzes the quality and the size of the strategic network of higher education institutions and the concept of fitness for purpose in quality assurance. It also analyses the transaction costs of networking that have consequences on the number of members in the network. Empirical evidence is presented from the Consortium on Applied Research and Professional Education, which is a European strategic network of six higher education institutions. The results of the study support the argument that the number of members in the strategic network should be relatively small to provide high-quality results. The practical importance is that networking has been able to promote international research and development projects. The results of this study are important for those who want to design and improve international networks in higher education.

Keywords: higher education, network, research and development, strategic management

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Authors: Sirapop Nuannimnoi, Hojjat Baghban, Ching-Yao Huang

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Over the past decade, with the fast development of blockchain technology since the birth of Bitcoin, there has been a massive increase in the usage of Cryptocurrencies. Cryptocurrencies are not seen as an investment opportunity due to the market’s erratic behavior and high price volatility. With the recent success of deep reinforcement learning (DRL), portfolio management can be modeled and automated. In this paper, we propose a novel DRL-based multi-agent system to automatically make proper trading decisions on multiple cryptocurrencies and gain profits in the highly volatile cryptocurrency market. We also extend this multi-agent system with horizontal federated transfer learning for better adapting to the inclusion of new cryptocurrencies in our portfolio; therefore, we can, through the concept of diversification, maximize our profits and minimize the trading risks. Experimental results through multiple simulation scenarios reveal that this proposed algorithmic trading system can offer three promising key advantages over other systems, including maximized profits, minimized risks, and adaptability.

Keywords: cryptocurrency portfolio management, algorithmic trading, federated learning, multi-agent reinforcement learning

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Authors: Okay Gunes

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Unsatisfactory experiences due to an information shortage regarding the future pay-offs of actual choices, yield satisficing decision-making. This research will examine, for the first time in the literature, the motivation behind suboptimal decisions due to uncertainty by subjecting Adam Smith’s and Jeremy Bentham’s assumptions about the nature of the actions that lead to satisficing behavior, in order to clarify the theoretical background of a “consumption-based satisfactory time” concept. The contribution of this paper with respect to the existing literature is threefold: Firstly, it is showed in this paper that Adam Smith’s uncertainty is related to the problem of the constancy of ideas and not related directly to beliefs. Secondly, possessions, as in Jeremy Bentham’s oeuvre, are assumed to be just as pleasing, as protecting and improving the actual or expected quality of life, so long as they reduce any displeasure due to the undesired outcomes of uncertainty. Finally, each consumption decision incurs its own satisfactory time period, owed to not feeling hungry, being healthy, not having transportation…etc. This reveals that the level of satisfaction is indeed a behavioral phenomenon where its value would depend on the simultaneous satisfaction derived from all activities.

Keywords: decision-making, idea and belief, satisficing, uncertainty

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Authors: Shun-Qi Zhang, Shu-Yang Zhang, Min Chen

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Applying strong electric field on piezoelectric actuators, on one hand very significant electroelastic material nonlinear effects will occur, on the other hand piezo plates and shells may undergo large displacements and rotations. In order to give a precise prediction of piezolaminated smart structures under large electric field, this paper develops a finite element (FE) model accounting for both electroelastic material nonlinearity and geometric nonlinearity with large rotations based on the first order shear deformation (FSOD) hypothesis. The proposed FE model is applied to analyze a piezolaminated semicircular shell structure.

Keywords: smart structures, piezolamintes, material nonlinearity, strong electric field

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Authors: John Michael Weber

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The following research results spanned six months and 175 people addicted to some form of substance, from alcohol to heroin. One question was asked, and the answers were amazing and consistent. The following work is the detailed results of this writer’s answer to his own question and the 175 that followed. A constant pattern took shape throughout the bio-psycho-social assessments, these addicts had “first memories,” the memories were vivid and took place between the ages of three to six years old, to a person those first memories were traumatic. This writer’s personal search into his childhood was not to find an excuse for the way he became, but to explain the reason for becoming an addict. To treat addiction, these memories that have caused Post Traumatic Stress Disorder (PTSD), must be recognized as the catalyst that sparked a predisposition. Cognitive Behavioral Therapy (CBT), integrated with treatment specifically focused on PTSD, gives the addict a better chance at recovery sans relapse. This paper seeks to give the findings of first memories of the addicts assessed and provide the best treatment plan for such an addict, considering, the childhood trauma in congruence with treatment of the Substance Use Disorder (SUD). The question posed was concerning what their first life memory wa It is the hope of this author to take the knowledge that trauma is one of the main catalysts for addiction, will allow therapists to provide better treatment and reduce relapse from abstinence from drugs and alcohol. This research led this author to believe that if treatment of childhood trauma is not a priority, the twelve steps of Alcoholics Anonymous, specifically steps 4 and 5, will not be thoroughly addressed and odds for relapse increase. With this knowledge, parents can be educated on childhood trauma and the effect it has on their children. Parents could be mindful of the fact that the things they perceive as traumatic, do not match what a child, in the developmental years, absorbs as traumatic. It is this author’s belief that what has become the status quo in treatment facilities has not been working for a long time. It is for that reason this author believes things need to change. Relapse has been woven into the fabric of standard operating procedure and that, in this authors view, is not necessary. Childhood Trauma is not being addressed early in recovery and that creates an environment of inevitable relapse. This paper will explore how to break away from the status -quo and rethink the current “evidencebased treatments.” To begin breaking away from status-quo, this ends the Abstract, with hopes an interest has been peaked to read on.

Keywords: childood, trauma, treatment, addiction, change

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Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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