Search results for: strengths-based approaches

Authors: Unal Atakan Kahraman, Yilmaz Uyaroğlu

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The chaotic signals generated by chaotic systems have some properties such as randomness, complexity and sensitive dependence on initial conditions, which make them particularly suitable for secure communications. Since the 1990s, the problem of secure communication, based on chaos synchronization, has been thoroughly investigated and many methods, for instance, robust and adaptive control approaches, have been proposed to realize the chaos synchronization. In this paper, an improved secure communication model is proposed based on control of supply chain management system. Control and masking communication simulation results are used to visualize the effectiveness of chaotic supply chain system also performed on the application of secure communication to the chaotic system. So, we discover the secure phenomenon of chaos-amplification in supply chain system

Keywords: chaotic analyze, control, secure communication, supply chain attractor

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Authors: Tessa Berg, Emma Guion Akdag

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Summative feedback forms are used in academia for gathering data on course quality and student understanding. Students answer a series of questions based on the course they are soon to finish in these forms. Feedback forms are notorious for being homogenised and limiting and thus the data captured is often neutral and lacking in tacit emotional responses. This paper contrasts student feedback forms with collaborative drawing. We analyse 19 pictures drawn by international students on a pre-sessional course. Through visuals we present an approach to enable a holistic level of student understanding. Visuals communicate irrespective of possible language, cultural and educational barriers. This paper sought to discover if the pictures mirrored the feedback given on a typical feedback form. Findings indicate a considerable difference in the two approaches and thus we highlight the value of collaborative drawing as a complimentary resource to aid the understanding of student experience.

Keywords: feedback forms, visualisation, student experience, collaborative drawing

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Authors: Sarah Majid Ansari, Serjosha Wulf, Matthias Goerke

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In times of global warming and the increasing shortage of resources, sustainable production is becoming more and more inevitable. Companies cannot only heighten their competitiveness but also contribute positively to environmental protection through efficient energy and resource consumption. Regarding this, technical solutions are often preferred during production, although organizational and process-related approaches also offer great potential. This project focuses on reducing resource usage, with a special emphasis on the human factor. It is the aspiration to develop a methodology that systematically implements and embeds suitable and individual measures and methods regarding resource efficiency throughout the entire production. The measures and methods established help employees handle resources and energy more sensitively. With this in mind, this paper also deals with the difficulties that can occur during the sensitization of employees and the implementation of these measures and methods. In addition, recommendations are given on how to avoid such difficulties.

Keywords: implementation, human factors, production plants, resource efficiency

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Authors: Nadia Ben Youssef, Aicha Bouzid

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Gradient estimation is one of the most fundamental tasks in the field of image processing in general, and more particularly for color images since that the research in color image gradient remains limited. The widely used gradient method is Di Zenzo’s gradient operator, which is based on the measure of squared local contrast of color images. The proposed gradient mechanism, presented in this paper, is based on the principle of the Di Zenzo’s approach using quaternion representation. This edge detector is compared to a marginal approach based on multiscale product of wavelet transform and another vector approach based on quaternion convolution and vector gradient approach. The experimental results indicate that the proposed color gradient operator outperforms marginal approach, however, it is less efficient then the second vector approach.

Keywords: gradient, edge detection, color image, quaternion

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Authors: Ilzira A. Minigalieva

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Assessment of cumulative health risks associated with the widely observed combined exposures to two or more metals and their compounds on the organism in industrial or general environment, as well as respective regulatory and technical risk management decision-making have presumably the theoretical and experimental toxicology of mixtures as their reliable scientific basis. Analysis of relevant literature and our own experience proves, however, that there is no full match between these different practices. Moreover, some of the contradictions between them are of a fundamental nature. This unsatisfactory state of things may be explained not only by unavoidable simplifications characteristic of the methodologies of risk assessment and permissible exposure standards setting but also by the extreme intrinsic complexity of the combined toxicity theory, the most essential issues of which are considered and briefly discussed in this paper.

Keywords: toxic metals, nanoparticles, typology of combined toxicity, mathematical modeling, health risk assessment and management

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Authors: Jonathan H. Westover, Jacque P. Westover, Maureen S. Andrade

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Though learning theories vary in complexity and usefulness, a thorough understanding of foundational learning theories is a necessity in today’s educational environment. Additionally, learning theories lead to approaches in instruction that can affect student motivation and learning. The combination of a learning theory and elements to enhance student motivation can create a learning context where the student can thrive in their educational pursuits. This paper will provide an overview of three main learning theories: (1) Behavioral Theory, (2) Cognitive Theory, and (3) Constructivist Theory and explore their connection to elements of student learning motivation. Finally, we apply these learning theories and elements of student motivation to the following two context: (1) The FastStart Program at the Community College of Denver, and (2) An Online Academic English Language Course. We discussed potential of the program and course to have success in increasing student success outcomes.

Keywords: learning theory, student motivation, inclusive pedagogy, developmental education

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Authors: Petra Hurbišová, Monika Davidová

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The article deals with the personality of military professionals (commanders) and their way of leading and commanding today and in historical context. The first part focuses on the leadership skills of Alexander the Great, who introduced strategic innovations and even from today's perspective he excelled in efficient work with people. This paper focuses on the way which he achieved his goals. Further attention is paid to approaches to commander´s personality by other great generals. The paper is also focused on personality traits of military professionals necessary for successful management and leadership in today's variable and challenging environment. Finally, attention is paid to the effective and ineffective ways of behavior of commanders and determined what styles of leadership is appropriate for a given situation, whether in peacetime or when commander is deployed in overseas operations or the state of war.

Keywords: authority, commander, leader, leadership, military professional, personality

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Authors: Nagmani Lnu

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Often, Quality Engineering refers to testing the applications that either have a User Interface (UI) or an Application Programming Interface (API). We often find mature test practices, standards, and automation regarding UI or API testing. However, another kind is present in almost all types of industries that deal with data in bulk and often get handled through something called a Batch Application. This is primarily an offline application companies develop to process large data sets that often deal with multiple business rules. The challenge gets more prominent when we try to automate batch testing. This paper describes the approaches taken to test a Batch application from a Financial Industry to test the payment settlement process (a critical use case in all kinds of FinTech companies), resulting in 100% test automation in Test Creation and Test execution. One can follow this approach for any other batch use cases to achieve a higher efficiency in their testing process.

Keywords: batch testing, batch test automation, batch test strategy, payments testing, payments settlement testing

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Authors: L. R. Valencia Pérez, J. M. Peña Aguilar, Valencia Pérez, Héctor Fernando, Lamadrid A. Alberto, Vivanco V. Martín

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Cosmology is a discipline commonly linked to philosophy. In this work, we show cosmology, from a perspective that can provide some proposals to help develop SMB in Mexico. We start from the belief that, in a complex world, the solutions to problems must nurture from different approaches. In order to be able to do this, we need to change our point of reference and use theoretical proposals and methodologies that came from other disciplines; in this case, we will try to show that between philosophy and administration exist dialogs that need to be incentivized. The work is structured in three parts. In the first one, we create a description of cosmology and how it could be applied to business. In the second, we show some of the most common problems that the SMB suffer from and in the third, we present a proposal of how cosmology can help improve the development. Finally, we concluded that better understanding of real needs, integration of knowledge at large scale and using information technologies within the cosmology framework presentment could make a difference.

Keywords: harmonic fusion, national sustainability, financial management, triple helix

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Authors: Benyamin Ahmadnia, Javier Serrano

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In this paper we compare two different approaches for translating from Persian to Spanish, as a language pair with scarce parallel corpus. The first approach involves direct transfer using an statistical machine translation system, which is available for this language pair. The second approach involves translation through English, as a pivot language, which has more translation resources and more advanced translation systems available. The results show that, it is possible to achieve better translation quality using English as a pivot language in either approach outperforms direct translation from Persian to Spanish. Our best result is the pivot system which scores higher than direct translation by (1.12) BLEU points.

Keywords: statistical machine translation, direct translation approach, pivot language translation approach, parallel corpus

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Authors: Mabrouka Morri, Amel Soualmia, Philippe Belleudy

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Vegetation affects the mean and turbulent flow structure. It may increase flood risks and sediment transport. Therefore, it is important to develop analytical approaches for the bed shear stress on vegetated bed, to predict resistance caused by vegetation. In the recent years, experimental and numerical models have both been developed to model the effects of submerged vegetation on open-channel flow. In this paper, different analytic models are compared and tested using the criteria of deviation, to explore their capacity for predicting the mean velocity and select the suitable one that will be applied in real case of rivers. The comparison between the measured data in vegetated flume and simulated mean velocities indicated, a good performance, in the case of rigid vegetation, whereas, Huthoff model shows the best agreement with a high coefficient of determination (R2=80%) and the smallest error in the prediction of the average velocities.

Keywords: analytic models, comparison, mean velocity, vegetation

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Authors: O. Anan, D. Böhning, A. Maruotti

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The purpose of the study is to estimate the elusive target population size under a truncated count model that accounts for heterogeneity. The purposed estimator is based on the generalized Poisson distribution (GPD), which extends the Poisson distribution by adding a dispersion parameter. Thus, it becomes an useful model for capture-recapture data where concurrent events are not homogeneous. In addition, it can account for over-dispersion and under-dispersion. The ratios of neighboring frequency counts are used as a tool for investigating the validity of whether generalized Poisson or Poisson distribution. Since capture-recapture approaches do not provide the zero counts, the estimated parameters can be achieved by modifying the EM-algorithm technique for the zero-truncated generalized Poisson distribution. The properties and the comparative performance of proposed estimator were investigated through simulation studies. Furthermore, some empirical examples are represented insights on the behavior of the estimators.

Keywords: capture, recapture methods, ratio plot, heterogeneous population, zero-truncated count

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Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

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The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: FSASEC, academic environment model, decision trees, k-nearest neighbor, machine learning, popularity index, support vector machine

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Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

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Authors: Sina Dehghani, Zhikang Rong

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Historically, a variety of approaches have been taken to forecast commodity prices due to the significant implications of these values on the global economy. An accurate forecasting tool for a valuable commodity would significantly benefit investors and governmental agencies. Silver, in particular, has grown significantly as a commodity in recent years due to its use in healthcare and technology. This manuscript aims to utilize the Geometric Brownian Motion predictive model to forecast silver commodity prices over multiple 3-year periods. The results of the study indicate that the model has several limitations, particularly its inability to work effectively over longer periods of time, but still was extremely effective over shorter time frames. This study sets a baseline for silver commodity forecasting with GBM, and the model could be further strengthened with refinement.

Keywords: geometric Brownian motion, commodity, risk management, volatility, stochastic behavior, price forecasting

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Authors: Arif Armagan Gozutok, Alper Kule, Burak Tos, Selman Demirel

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Wireless communication chain requires effective ways to keep throughput efficiency high while it suffers location-dependent, time-varying burst errors. Several techniques are developed in order to assure that the receiver recovers the transmitted information without errors. The most fundamental approaches are error checking and correction besides re-transmission of the non-acknowledged packets. In this paper, stop & wait (SAW) and chase combined (CC) hybrid automated repeat request (HARQ) protocols are compared and analyzed in terms of throughput and average delay for the usage of low earth orbit (LEO) mega-constellations case. Several assumptions and technological implementations are considered as well as usage of low-density parity check (LDPC) codes together with several constellation orbit configurations.

Keywords: HARQ, LEO, satellite constellation, throughput

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Authors: Ahmad Aslizadeh, Farid Ghaderi

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Mapping organizational knowledge is an innovative concept and useful instrument of representation, capturing and visualization of implicit and explicit knowledge. There are a diversity of methods, instruments and techniques presented by different researchers following mapping organizational knowledge to reach determined goals. Implicating of these methods, it is necessary to know their exigencies and conditions in which those can be used. Integrating identified methods of knowledge mapping and comparing them would help knowledge managers to select the appropriate methods. This research conducted to presenting a model and framework to map organizational knowledge. At first, knowledge maps, their applications and necessity are introduced because of extracting comparative framework and detection of their structure. At the next step techniques of researchers such as Eppler, Kim, Egbu, Tandukar and Ebner as knowledge mapping models are presented and surveyed. Finally, they compare and a superior model would be introduced.

Keywords: knowledge mapping, knowledge management, comparative study, business and management

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Authors: Fazl E. Ahad, Shi Dongyan, Anees Ur Rehman

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Plates are one of the most important structural components used in many industries like aerospace, marine and various other engineering fields and thus motivate designers and engineers to study the vibrational characteristics of these structures. This paper is a review of existing literature on vibration analysis of plates. Focus has been kept on prominent studies related to isotropic plates based on Mindlin plate theory; however few citations on orthotropic plates and higher order shear deformation theories have also been included. All citations are in English language. This review is aimed to provide contemporarily relevant survey of papers on vibrational characteristics of thick plates and will be useful for scientists, designers and researchers to locate important and relevant literature/research quickly.

Keywords: mindlin plates, vibrations, arbitrary boundary conditions, mode shapes, natural frequency

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Authors: Raza Ullah, Hazir Ullah

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There is ample evidence that reveals the outstanding performance of girls in a different range of subjects. However, it is pertinent to mention here that boys have historically dominated girls, particularly in math, physics, and technological subjects across the globe with the exception of few developed countries. This article examines the reasons why girls are underdog in STEM subjects. The article critically analyzes two main approaches towards gender and education: biological determinist and feminist. This article highlights that social factors influencing girls performance in STEM subjects have not analyzed critically, and girls underachieving in science has linked with biological and sex differences. The article concludes that the underperformance of girls in a STEM subject is the direct response of socio-cultural factors. Thus, socio-cultural factors are responsible for the dearth of girls in STEM subjects.

Keywords: gender, underperformance, STEM, education, sex

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Authors: Ijaz Ahmed, Anwar Zada, Muhammad Waqas, M. U. Ashraf

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We demonstrate the performance of a very efficient tagger applies on hadronically decaying top quark pairs as signal based on deep neural network algorithms and compares with the QCD multi-jet background events. A significant enhancement of performance in boosted top quark events is observed with our limited computing resources. We also compare modern machine learning approaches and perform a multivariate analysis of boosted top-pair as well as single top quark production through weak interaction at √s = 14 TeV proton-proton Collider. The most relevant known background processes are incorporated. Through the techniques of Boosted Decision Tree (BDT), likelihood and Multlayer Perceptron (MLP) the analysis is trained to observe the performance in comparison with the conventional cut based and count approach

Keywords: top tagger, multivariate, deep learning, LHC, single top

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Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan

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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.

Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM

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Authors: Josef Uher, Jana Boháčová, Richard Kadeřábek

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In this paper, we present a multi-robot imaging and irradiation research platform referred to as Irradion, with full capabilities of portable arbitrary path computed tomography (CT). Irradion is an imaging and irradiation unit entirely based on robotic arms for research on cancer treatment with ion beams on small animals (mice or rats). The platform comprises two subsystems that combine several imaging modalities, such as 2D X-ray imaging, CT, and particle tracking, with precise positioning of a small animal for imaging and irradiation. Computed Tomography: The CT subsystem of the Irradion platform is equipped with two 6-joint robotic arms that position a photon counting detector and an X-ray tube independently and freely around the scanned specimen and allow image acquisition utilizing computed tomography. Irradiation measures nearly all conventional 2D and 3D trajectories of X-ray imaging with precisely calibrated and repeatable geometrical accuracy leading to a spatial resolution of up to 50 µm. In addition, the photon counting detectors allow X-ray photon energy discrimination, which can suppress scattered radiation, thus improving image contrast. It can also measure absorption spectra and recognize different materials (tissue) types. X-ray video recording and real-time imaging options can be applied for studies of dynamic processes, including in vivo specimens. Moreover, Irradion opens the door to exploring new 2D and 3D X-ray imaging approaches. We demonstrate in this publication various novel scan trajectories and their benefits. Proton Imaging and Particle Tracking: The Irradion platform allows combining several imaging modules with any required number of robots. The proton tracking module comprises another two robots, each holding particle tracking detectors with position, energy, and time-sensitive sensors Timepix3. Timepix3 detectors can track particles entering and exiting the specimen and allow accurate guiding of photon/ion beams for irradiation. In addition, quantifying the energy losses before and after the specimen brings essential information for precise irradiation planning and verification. Work on the small animal research platform Irradion involved advanced software and hardware development that will offer researchers a novel way to investigate new approaches in (i) radiotherapy, (ii) spectral CT, (iii) arbitrary path CT, (iv) particle tracking. The robotic platform for imaging and radiation research developed for the project is an entirely new product on the market. Preclinical research systems with precision robotic irradiation with photon/ion beams combined with multimodality high-resolution imaging do not exist currently. The researched technology can potentially cause a significant leap forward compared to the current, first-generation primary devices.

Keywords: arbitrary path CT, robotic CT, modular, multi-robot, small animal imaging

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Authors: Amon Olimov, Umarov Jamshid, Dae-Ho Kim, Chol-U Lee, Ryum-Duck Oh

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This paper proposes IoT virtualization platform based incident information system. IoT information based environment is the platform that was developed for the purpose of collecting a variety of data by managing regionally scattered IoT devices easily and conveniently in addition to analyzing data collected from roads. Moreover, this paper configured the platform for the purpose of providing incident information based on sensed data. It also provides the same input/output interface as UNIX and Linux by means of matching IoT devices with the directory of file system and also the files. In addition, it has a variety of approaches as to the devices. Thus, it can be applied to not only incident information but also other platforms. This paper proposes the incident information system that identifies and provides various data in real time as to urgent matters on roads based on the existing USN/M2M and IoT visualization platform.

Keywords: incident information system, IoT, virtualization platform, USN, M2M

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Authors: Mohan T. Harish, Masson Lauriane, Sreevalsa Kolathayar

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Environmental issues raise alarm in the constructional field which implies a need for exploring new construction materials derived from the waste and residual products. This paper presents a detailed review of the alternatives approaches employed in the construction field using plastic waste in mixture with mixed with fillers. A detailed analysis of the plastic waste used in concrete, with soil, sand, clay and natural residues like sawdust, rice husk etc are presented. The different process carried forward was also discussed along with the scrutiny of the change in mechanical properties. The effect of coupling agents in the proposed mixture has been appraised in detail which gives implications for its future application in the field of plastic waste with viable materials in composite construction blocks.

Keywords: plastic waste, composite materials, construction block, concrete, natural residue, coupling agent

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Authors: Asghar Ali, Narjis Khatoon

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This study focuses on the presence of wage differentials in Pakistan and also on the determinants that originate it. Since there are a smaller number of studies that are conducted on this topic in Pakistan, the current study aims to contribute in bridging the existing gap in this particular research genre. Hence, this study not only generates the desired results specific focus but it also contributes to the overall empirical work on the Pakistan economy. The preceding works which have been done to research wage determinants and wage differentials have used numerous different theories and approaches to reach their goals. The current study, in order to analyze the determinants of wage differentials in the developing economy, deals with the study of a number of such theories and approaches that are supposed as being beneficial for the purpose. This study undertakes the explanation of wage differentials in Pakistan by focusing on wage differentials in public and private sectors, formal and informal sectors, and major occupational groups. The study uses 'Wage Theory' to examine wage differentials among male and female employees in public and private sectors on varied levels of working conditions. This study also uses 'Segmented Labor Market Theory' to determine the wage differential in both public and private sectors, formal and informal, and major occupational groups in Pakistan. So the author has used various econometric techniques in order to explain and test these theories and to find out the required results. This study has employed seven different cross-sectional Labour Force Surveys for the time period between 2006-07 to 2012-13. Gender equality is not only a policy reform agenda for developing countries but also an important goal of Millennium Development Goals. This study investigates the nexus between wage inequality and economic growth and detects co-integration between gender wage differential and economic growth using ARDL bound test. It is confirmed from the empirical results that there exists long-run relationship between economic growth and wage differential. Our study indicated that half of the total female employees from fourteen major cities of Pakistan were employed in the public sector. Out of total female employees in private sector, 66 percent are employed in the formal sector, and 33 percent are working in the informal sector. Results also indicated that both men and women were paid more in the public sector compared to the private sector counterparts. Among the total female employees, only 9 percent had received any formal training, 52% were married and average years of schooling were 11 years. Further, our findings regarding wage differential between genders indicate that wage gap is lower in public sector as compared to private sector. In proportion, gender wage ratio was found to be 0.96, 0.62 and 0.66 in public, formal private and informal private sectors respectively. This suggests that in this case, private sector female employees with the same pay structure are compensated at a lower endowments rate as then public sector workers as compared to their counter parts.

Keywords: wage differentials, formal, informal, economic growth

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Authors: Amar Ghelani

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People with auditory verbal hallucinations (AVH) who seek support from mental health services commonly report feeling unheard and invalidated in their interactions with social workers and psychiatric professionals. Current mental health training and clinical approaches have proven to be inadequate in addressing the complex nature of voice hearing. Childhood trauma is a key factor in the development of AVH and can render people more vulnerable to hearing both supportive and/or disturbing voices. Lived experiences of racism, poverty, and immigration are also associated with development of what is broadly classified as psychosis. Despite evidence affirming the influence of environmental factors on voice hearing, the Western biomedical system typically conceptualizes this experience as a symptom of genetically-based mental illnesses which requires diagnosis and treatment. Overemphasis on psychiatric medications, referrals, and directive approaches to people’s problems has shifted clinical interventions away from assessing and addressing problems directly related to AVH. The Maastricht approach offers voice hearers and mental health workers an alternative and respectful starting point for understanding and coping with voices. The approach was developed by voice hearers in partnership with mental health professionals and entails an innovative method to assess and create meaning from voice hearing and related life stressors. The objectives of the approach are to help people who hear voices: (1) understand the problems and/or people the voices may represent in their history, and (2) cope with distress and find solutions to related problems. The Maastricht approach has also been found to help voice hearers integrate emotional conflicts, reduce avoidance or fear associated with AVH, improve therapeutic relationships, and increase a sense of control over internal experiences. The proposed oral presentation will be guided by a recovery-oriented theoretical framework which suggests healing from psychological wounds occurs through social connections and community support systems. The presentation will start with a brainstorming exercise to identify participants pre-existing knowledge of the subject matter. This will lead into a literature review on the relations between trauma, intersectionality, and AVH. An overview of the Maastricht approach and review of research related to its therapeutic risks and benefits will follow. Participants will learn trauma-informed coping skills and questions which can help voice hearers make meaning from their experiences. The presentation will conclude with a review of resources and learning opportunities where participants can expand their knowledge of the Hearing Voices Movement and Maastricht approach.

Keywords: Maastricht interview, recovery, therapeutic assessment, voice hearing

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

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Authors: Igor V. Grigoriev

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Understanding of biological processes encoded in fungi is instrumental in addressing future food, feed, and energy demands of the growing human population. Genomics is a powerful and quickly evolving tool to understand these processes. The Fungal Genomics Program of the US Department of Energy Joint Genome Institute (JGI) partners with researchers around the world to explore fungi in several large scale genomics projects, changing the fungal genomics landscape. The key trends of these changes include: (i) rapidly increasing scale of sequencing and analysis, (ii) developing approaches to go beyond culturable fungi and explore fungal ‘dark matter,’ or unculturables, and (iii) functional genomics and multi-omics data integration. Power of comparative genomics has been recently demonstrated in several JGI projects targeting mycorrhizae, plant pathogens, wood decay fungi, and sugar fermenting yeasts. The largest JGI project ‘1000 Fungal Genomes’ aims at exploring the diversity across the Fungal Tree of Life in order to better understand fungal evolution and to build a catalogue of genes, enzymes, and pathways for biotechnological applications. At this point, at least 65% of over 700 known families have one or more reference genomes sequenced, enabling metagenomics studies of microbial communities and their interactions with plants. For many of the remaining families no representative species are available from culture collections. To sequence genomes of unculturable fungi two approaches have been developed: (a) sequencing DNA from fruiting bodies of ‘macro’ and (b) single cell genomics using fungal spores. The latter has been tested using zoospores from the early diverging fungi and resulted in several near-complete genomes from underexplored branches of the Fungal Tree, including the first genomes of Zoopagomycotina. Genome sequence serves as a reference for transcriptomics studies, the first step towards functional genomics. In the JGI fungal mini-ENCODE project transcriptomes of the model fungus Neurospora crassa grown on a spectrum of carbon sources have been collected to build regulatory gene networks. Epigenomics is another tool to understand gene regulation and recently introduced single molecule sequencing platforms not only provide better genome assemblies but can also detect DNA modifications. For example, 6mC methylome was surveyed across many diverse fungi and the highest among Eukaryota levels of 6mC methylation has been reported. Finally, data production at such scale requires data integration to enable efficient data analysis. Over 700 fungal genomes and other -omes have been integrated in JGI MycoCosm portal and equipped with comparative genomics tools to enable researchers addressing a broad spectrum of biological questions and applications for bioenergy and biotechnology.

Keywords: fungal genomics, single cell genomics, DNA methylation, comparative genomics

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Authors: Maria Cristina B. Cabanag, Elijinese Marie S. Culangen

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Pregnancy is a period in a woman's life wherein the body may undergo different physiological changes. These changes can be attributed to the interplay of hormones in the body but can mask a more sinister type of disease such as malignancy on rare occasions. Colorectal cancer (CRC) in pregnancy is an epidemiologically rare disease worldwide. To our knowledge, no available studies were reported in the Philippines at the time of this writing, posing a dilemma for its appropriate diagnosis and management. Signs and symptoms of colorectal malignancy may camouflage a normal pregnancy and, when overlooked, impedes an appropriate approach. This case of a 38-year-old elderly primigravid who presented with hematochezia on her 25th week of gestation. She was diagnosed with rectal adenocarcinoma later in pregnancy which warranted a predicament regarding her appropriate care and management. This paper explores the repertoire of the different diagnostic and treatment approaches to colorectal cancer in the second trimester of pregnancy, with the least possible maternal and fetal hazards.

Keywords: cancer in pregnancy, chemotherapy in pregnancy, colorectal cancer, hematochezia in pregnancy

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Authors: Sima Najafzadehkhoei, George Vega Yon

Abstract:

This paper presents an approach for calibrating Agent-Based Models (ABMs) efficiently, utilizing Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. These machine learning techniques are applied to Susceptible-Infected-Recovered (SIR) models, which are a core framework in the study of epidemiology. Our method replicates parameter values from observed trajectory curves, enhancing the accuracy of predictions when compared to traditional calibration techniques. Through the use of simulated data, we train the models to predict epidemiological parameters more accurately. Two primary approaches were explored: one where the number of susceptible, infected, and recovered individuals is fully known, and another using only the number of infected individuals. Our method shows promise for application in other ABMs where calibration is computationally intensive and expensive.

Keywords: ABM, calibration, CNN, LSTM, epidemiology

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