Search results for: Combined process.

Authors: B. Al-Naami, N. Gharaibeh, A. AlRazzaq Kheshman

Abstract:

Alzheimer is known as the loss of mental functions such as thinking, memory, and reasoning that is severe enough to interfere with a person's daily functioning. The appearance of Alzheimer Disease symptoms (AD) are resulted based on which part of the brain has a variety of infection or damage. In this case, the MRI is the best biomedical instrumentation can be ever used to discover the AD existence. Therefore, this paper proposed a fusion method to distinguish between the normal and (AD) MRIs. In this combined method around 27 MRIs collected from Jordanian Hospitals are analyzed based on the use of Low pass -morphological filters to get the extracted statistical outputs through intensity histogram to be employed by the descriptive box plot. Also, the artificial neural network (ANN) is applied to test the performance of this approach. Finally, the obtained result of t-test with confidence accuracy (95%) has compared with classification accuracy of ANN (100 %). The robust of the developed method can be considered effectively to diagnose and determine the type of AD image.

Keywords: Alzheimer disease, Brain MRI analysis, Morphological filter, Box plot, Intensity histogram, ANN.

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Authors: A. Zimnas, D. Kleftouris, N. Valkanos

Abstract:

Today-s Information and Knowledge Society has placed new demands on education and a new paradigm of education is required. Learning, facilitated by educational systems and the pedagogic process, is globally undergoing dramatic changes. The aim of this paper is the development of a simple Instructional Design tool for E-Learning, named IDEL (Instructional Design for Electronic Learning), that provides the educators with facilities to create their own courses with the essential educational material and manage communication with students. It offers flexibility in the way of learning and provides ease in employment and reusability of resources. IDEL is a web-based Instructional System and is designed to facilitate course design process in accordance with the ADDIE model and the instructional design principles with emphasis placed on the use of technology enhanced learning. An example case of using the ADDIE model to systematically develop a course and its implementation with the aid of IDEL is given and some results from student evaluation of the tool and the course are reported.

Keywords: Education, E-learning, Instructional Design.

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Authors: A.G.E. Sutjipto, Jufriadi, R. Muhida, Afzeri, E.Y. Adesta

Abstract:

Charging and discharging phenomenon on the surface of materials can be found in plasma display panel, spacecraft charging, high voltage insulator, etc. This report gives a simple explanation on this phenomenon. A scanning electron microscope was used not only as a tool to produce energetic electron beam to charge an insulator without metallic coating and to produce a surface discharging (surface breakdown/flashover) but also to observe the visible charging and discharging on the sample surface. A model of electric field distribution on the surface was developed in order to explain charging and discharging phenomena. Since charging and discharging process involves incubation time, therefore this process can be used to evaluate the insulation property of materials under electron bombardment.

Keywords: Flashover, SEM, Electron Bombardment, Electric Field.

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Authors: Hassan Haghighi, Omid Mafi

Abstract:

Existing experiences indicate that one of the most prominent reasons that some ERP implementations fail is related to selecting an improper ERP package. Among those important factors resulting in inappropriate ERP selections, one is to ignore preliminary activities that should be done before the evaluation of ERP packages. Another factor yielding these unsuitable selections is that usually organizations employ prolonged and costly selection processes in such extent that sometimes the process would never be finalized or sometimes the evaluation team might perform many key final activities in an incomplete or inaccurate way due to exhaustion, lack of interest or out-of-date data. In this paper, a systematic approach that recommends some activities to be done before and after the main selection phase is introduced for choosing an ERP package. On the other hand, the proposed approach has utilized some ideas that accelerates the selection process at the same time that reduces the probability of an erroneous final selection.

Keywords: enterprise resource planning, evaluation and selectionof ERP packages, organizational readiness for employing ERP, evaluationlists.

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Authors: Xinyue Zhao, Yutaka Satoh, Hidenori Takauji, Shun'ichi Kaneko

Abstract:

A hybrid feature based adaptive particle filter algorithm is presented for object tracking in real scenarios with static camera. The hybrid feature is combined by two effective features: the Grayscale Arranging Pairs (GAP) feature and the color histogram feature. The GAP feature has high discriminative ability even under conditions of severe illumination variation and dynamic background elements, while the color histogram feature has high reliability to identify the detected objects. The combination of two features covers the shortage of single feature. Furthermore, we adopt an updating target model so that some external problems such as visual angles can be overcame well. An automatic initialization algorithm is introduced which provides precise initial positions of objects. The experimental results show the good performance of the proposed method.

Keywords: Hybrid feature, adaptive Particle Filter, robust Object Tracking, Grayscale Arranging Pairs (GAP) feature.

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Authors: H.Mohammadi Majd, M.Jalali Azizpour, M. Goodarzi

Abstract:

In this paper back-propagation artificial neural network (BPANN) with Levenberg–Marquardt algorithm is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.

Keywords: BPANN, deep drawing, prediction, limiting drawingratio (LDR), Levenberg–Marquardt algorithm

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Authors: Pin-Hsu Kao, Wen-Shou Tseng, Hung-Ming Tai, Yuan-Ming Chang, Jenh-Yih Juang

Abstract:

We report a lithography-free approach to fabricate the biomimetics, quasi-beehive Si nanostructures (QBSNs), on Si-substrates. The self-assembled SiGe nanoislands via the strain induced surface roughening (Asaro-Tiller-Grinfeld instability) during in-situ annealing play a key role as patterned sacrifice regions for subsequent reactive ion etching (RIE) process performed for fabricating quasi-beehive nanostructures on Si-substrates. As the measurements of field emission, the bare QBSNs show poor field emission performance, resulted from the existence of the native oxide layer which forms an insurmountable barrier for electron emission. In order to dramatically improve the field emission characteristics, the platinum nanopillars (Pt-NPs) were deposited on QBSNs to form Pt-NPs/QBSNs heterostructures. The turn-on field of Pt-NPs/QBSNs is as low as 2.29 V/μm (corresponding current density of 1 μA/cm2), and the field enhancement factor (β-value) is significantly increased to 6067. More importantly, the uniform and continuous electrons excite light emission, due to the surrounding filed emitters from Pt-NPs/QBSNs, can be easily obtained. This approach does not require an expensive photolithographic process and possesses great potential for applications.

Keywords: Biomimetics, quasi-beehive Si, SiGe nanoislands, platinum nanopillars, field emission.

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Authors: Mahmoud M. Tash

Abstract:

The present study was carried out to investigate the effect of alloying elements and thermo-mechanical treatment (TMT) i.e. hot rolling and forging with different reduction ratios on the hardness (HV) and impact toughness (J) of heat-treated low alloy steels. An understanding of the combined effect of TMT and alloying elements and by measuring hardness, impact toughness, resulting from different heat treatment following TMT of the low alloy steels, it is possible to determine which conditions yielded optimum mechanical properties and high strength to weight ratio. Experimental Correlations between hot work reduction ratio, hardness and impact toughness for thermo-mechanically heat treated low alloy steels are analyzed quantitatively, and both regression and mathematical hardness and impact toughness models are developed.

Keywords: Hot Forging, hot rolling, heat treatment, hardness (hv), impact toughness (j), microstructure, low alloy steels.

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Authors: Armansyah, I. P. Almanar, M. Saiful Bahari Shaari, M. Shamil Jaffarullah, Nur’amirah Busu, M. Arif Fadzleen Zainal Abidin, M. Amlie A. Kasim

Abstract:

During welding, the amount of heat present in weld zones determines the quality of weldment produced. Thus, the heat distribution characteristics and its magnitude in weld zones with respect to process variables such as tool pin-shoulder rotational and traveling speed during welding is analyzed using thermal finite element analyses method. For this purpose, transient thermal finite element analyses are performed to model the temperatures distribution and its quantities in weld-zones with respect to process variables such as rotational speed and traveling speed during welding. Commercially available software Altair HyperWork is used to model three-dimensional tool pin-shoulder vs. workpieces and to simulate the friction stir process. The results show that increasing tool rotational speed, at a constant traveling speed, will increase the amount of heat generated in weld-zones. In contrary, increasing traveling speed, at constant tool pin-shoulder rotational speeds, will reduce the amount of heat generated in weld zones.

Keywords: Frictions Stir Welding, Temperature Distribution, Finite Element Method, Altair Hyperwork.

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Authors: Baghdasaryan Marinka, Ulikyan Azatuhi

Abstract:

The efficient usage of the compensation abilities of the electrical drive synchronous motors used in production processes can essentially improve the technical and economic indices of the process.  Reducing the flows of the reactive electrical energy due to the compensation of reactive power allows to significantly reduce the load losses of power in the electrical networks. As a result of analyzing the scientific works devoted to the issues of regulating the excitation of the synchronous motors, the need for comprehensive investigation and estimation of the excitation mode has been substantiated. By means of the obtained transmission functions, in the Simulink environment of the software package MATLAB, the transition processes of the excitation mode have been studied. As a result of obtaining and estimating the graph of the Nyquist plot and the transient process, the necessity of developing the Proportional-Integral-Derivative (PID) regulator has been justified. The transient processes of the system of the PID regulator have been investigated, and the amplitude–phase characteristics of the system have been estimated. The analysis of the obtained results has shown that the regulation indices of the developed system have been improved. The developed system can be successfully applied for regulating the excitation voltage of different-power synchronous motors, operating with a changing load, ensuring a value of the power coefficient close to 1.

Keywords: Transient process, synchronous motor, excitation mode, regulator, reactive power.

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Authors: G. Bago, P. Hedbávný

Abstract:

This contribution was developed from a research within the doctoral thesis. Its object was to create multimedia materials for sport gymnastics. Consequently we surveyed the influence of its practical application on the efficiency of schooling at a university. We verified the prescribed hypothesis of the efficiency of the teaching process using the method of single-factor experiment, where the entrance independent variable was the change of system of tuition and the outgoing dependent variable was the change of level of acquired motor skills. The results confirmed the positive impact of using multimedia materials on the efficiency of the teaching process. Further, with the aid of questionnaires, we evaluated how the tested subjects perceive the innovative methods in sport gymnastics. The responses showed that the students rate the application of multimedia materials very positively.

Keywords: efficiency of education, means of education, multimedia materials, sports gymnastics

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Authors: L. Bikulciene, E. Venskaityte, G. Jarusevicius

Abstract:

Nonstationary and nonlinear signals generated by living complex systems defy traditional mechanistic approaches, which are based on homeostasis. Previous our studies have shown that the evaluation of the interactions of physiological signals by using special analysis methods is suitable for observation of physiological processes. It is demonstrated the possibility of using deep physiological model, based on the interpretation of the changes of the human body’s functional states combined with an application of the analytical method based on matrix theory for the physiological signals analysis, which was applied on high risk cardiac patients. It is shown that evaluation of cardiac signals interactions show peculiar for each individual functional changes at the onset of hemodynamic restoration procedure. Therefore, we suggest that the alterations of functional state of the body, after patients overcome surgery can be complemented by the data received from the suggested approach of the evaluation of functional variables’ interactions.

Keywords: Cardiac diseases, Complex systems theory, ECG analysis, matrix analysis.

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Authors: Yi Chao Huang, Yu Ling Liao, Chiu Shuang Lin

Abstract:

A data cutting and sorting method (DCSM) is proposed to optimize the performance of data mining. DCSM reduces the calculation time by getting rid of redundant data during the data mining process. In addition, DCSM minimizes the computational units by splitting the database and by sorting data with support counts. In the process of searching for the relationship between metabolic syndrome and lifestyles with the health examination database of an electronics manufacturing company, DCSM demonstrates higher search efficiency than the traditional Apriori algorithm in tests with different support counts.

Keywords: Data mining, Data cutting and sorting method, Apriori algorithm, Metabolic syndrome

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Authors: Nabli L., Dhouibi H., Collart Dutilleul S., Craye E.

Abstract:

The indistinctness of the manufacturing processes makes that a parts cannot be realized in an absolutely exact way towards the specifications on the dimensions. It is thus necessary to assume that the effectively realized product has to belong in a very strict way to compatible intervals with a correct functioning of the parts. In this paper we present an approach based on mixing tow different characteristics theories, the fuzzy system and Petri net system. This tool has been proposed to model and control the quality in an assembly system. A robust command of a mechanical assembly process is presented as an application. This command will then have to maintain the specifications interval of parts in front of the variations. It also illustrates how the technique reacts when the product quality is high, medium, or low.

Keywords: Petri nets, production rate, performance evaluation, tolerant system, fuzzy sets.

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Authors: Mahesh K. Chudasama, Harit K. Raval

Abstract:

3-roller conical bending process is widely used in the industries for manufacturing of conical sections and shells. It involves static as well dynamic bending stages. Analytical models for prediction of bending force during static as well as dynamic bending stage are available in the literature. In this paper bending forces required for static bending stage and dynamic bending stages have been compared using the analytical models. It is concluded that force required for dynamic bending is very less as compared to the bending force required during the static bending stage.

Keywords: Analytical modeling, cone frustum, dynamic bending, static bending.

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Authors: N. M. Nawi, R. S. Ransing, M. R. Ransing

Abstract:

The conjugate gradient optimization algorithm is combined with the modified back propagation algorithm to yield a computationally efficient algorithm for training multilayer perceptron (MLP) networks (CGFR/AG). The computational efficiency is enhanced by adaptively modifying initial search direction as described in the following steps: (1) Modification on standard back propagation algorithm by introducing a gain variation term in the activation function, (2) Calculation of the gradient descent of error with respect to the weights and gains values and (3) the determination of a new search direction by using information calculated in step (2). The performance of the proposed method is demonstrated by comparing accuracy and computation time with the conjugate gradient algorithm used in MATLAB neural network toolbox. The results show that the computational efficiency of the proposed method was better than the standard conjugate gradient algorithm.

Keywords: Adaptive gain variation, back-propagation, activation function, conjugate gradient, search direction.

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Authors: Carlos Ferreira, Paulo Freitas, Valentim Freitas

Abstract:

Creative industries’ workers are becoming more prominent as countries move towards intellectual-based economies. Consequently, the nature and essence of the workplace needs to be reconfigured so that creativity and productivity can be better promoted at these spaces. Using a multidisciplinary approach and a user-centered methodology, combining product design, electronic engineering, software and human-computer interaction, we have designed and developed a new seat that uses embedded sensors and actuators to increase the overall well-being of its users, their productivity and their creativity. Our contribution focuses on the parameters that most affect the user’s work on these kinds of spaces, which are, according to our study, noise and temperature. We describe the design process for a new interactive seat targeted at improving workspace productivity.

Keywords: Human-computer interaction, usability, user interface, creativity, ergonomics.

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Authors: Ek Ngoy, A F Mulaba-Bafubiandi

Abstract:

Cobalt was acid nitric leached from a mixed cobaltcopper oxide with variable acid concentration. Resulting experimental data were used to analyze effects of increase in acid concentration, based on a shrinking core model of the process. The mathematical simulation demonstrated that the time rate of the dissolution mechanism is an increasing function of acid concentration. It was also shown that the magnitude of the acid concentration effect is time dependent and the increase in acid concentration is more effective at earlier stage of the dissolution than at later stage. The remaining process parameters are comprehensively affected by acid concentration and their interaction is synergetic.

Keywords: Acid effect, Cobalt, Cobalt-copper oxide, Leaching, Simulation

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Authors: Nebi Gedik

Abstract:

One of the important parts of the brain-computer interface (BCI) studies is the classification of motor imagery (MI) obtained by electroencephalography (EEG). The major goal is to provide non-muscular communication and control via assistive technologies to people with severe motor disorders so that they can communicate with the outside world. In this study, an EEG signal classification approach based on multiscale and multi-resolution transform method is presented. The proposed approach is used to decompose the EEG signal containing motor image information (right- and left-hand movement imagery). The decomposition process is performed using curvelet transform which is a multiscale and multiresolution analysis method, and the transform output was evaluated as feature data. The obtained feature set is subjected to feature selection process to obtain the most effective ones using t-test methods. SVM and k-NN algorithms are assigned for classification.

Keywords: motor imagery, EEG, curvelet transform, SVM, k-NN

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Authors: Morteza Khaleghi, Babak Seyed Aghazadeh, Hosein Bisadi

Abstract:

Oxyhydrogen is a mixture of Hydrogen (H₂) and Oxygen (O₂) gases. Detonative mixtures of oxyhydrogens with various combinations of these two gases were used in Gas Detonation Forming (GDF) to form sheets of mild steel. In die forming experiments, three types of conical dies with apex angles of 60, 90 and 120 degrees were used. Pressure of mixtures inside the chamber before detonation was varied from 3 Bar to 5 Bar to investigate the effect of pre-detonation pressure in the forming process. On each conical die, several experiments with different percentages of Hydrogen were carried out to determine the optimum gaseous mixture. According to our results the best forming process occurred when approximately 50-70%. Hydrogen was employed in the mixture. Furthermore, the experimental results were compared to the ones from FEM analysis. The FEM simulation results of thickness strain, hoop strain, thickness variation and deformed geometry are promising.

Keywords: Sheet metal forming, Gas detonation, FEM, Oxyhydrogen

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Authors: B. Arun Kumar, T. Ravichandran

Abstract:

Workflow scheduling is an important part of cloud computing and based on different criteria it decides cost, execution time, and performances. A cloud workflow system is a platform service facilitating automation of distributed applications based on new cloud infrastructure. An aspect which differentiates cloud workflow system from others is market-oriented business model, an innovation which challenges conventional workflow scheduling strategies. Time and Cost optimization algorithm for scheduling Hybrid Clouds (TCHC) algorithm decides which resource should be chartered from public providers is combined with a new De-De algorithm considering that every instance of single and multiple workflows work without deadlocks. To offset this, two new concepts - De-De Dodging Algorithm and Priority Based Decisive Algorithm - combine with conventional deadlock avoidance issues by proposing one algorithm that maximizes active (not just allocated) resource use and reduces Makespan.

Keywords: Workflow Scheduling, cloud workflow, TCHC algorithm, De-De Dodging Algorithm, Priority Based Decisive Algorithm (PBD), Makespan.

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Authors: Pichet Sriyanyong

Abstract:

This paper presents the application of an enhanced Particle Swarm Optimization (EPSO) combined with Gaussian Mutation (GM) for solving the Dynamic Economic Dispatch (DED) problem considering the operating constraints of generators. The EPSO consists of the standard PSO and a modified heuristic search approaches. Namely, the ability of the traditional PSO is enhanced by applying the modified heuristic search approach to prevent the solutions from violating the constraints. In addition, Gaussian Mutation is aimed at increasing the diversity of global search, whilst it also prevents being trapped in suboptimal points during search. To illustrate its efficiency and effectiveness, the developed EPSO-GM approach is tested on the 3-unit and 10-unit 24-hour systems considering valve-point effect. From the experimental results, it can be concluded that the proposed EPSO-GM provides, the accurate solution, the efficiency, and the feature of robust computation compared with other algorithms under consideration.

Keywords: Particle Swarm Optimization (PSO), GaussianMutation (GM), Dynamic Economic Dispatch (DED).

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Authors: Abdalla Kablan, Joseph Falzon

Abstract:

This paper is motivated by the aspect of uncertainty in financial decision making, and how artificial intelligence and soft computing, with its uncertainty reducing aspects can be used for algorithmic trading applications that trade in high frequency. This paper presents an optimized high frequency trading system that has been combined with various moving averages to produce a hybrid system that outperforms trading systems that rely solely on moving averages. The paper optimizes an adaptive neuro-fuzzy inference system that takes both the price and its moving average as input, learns to predict price movements from training data consisting of intraday data, dynamically switches between the best performing moving averages, and performs decision making of when to buy or sell a certain currency in high frequency.

Keywords: Financial decision making, High frequency trading, Adaprive neuro-fuzzy systems, moving average strategy.

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Authors: Mounir Zekkaoui, Abdelhadi Fennan

Abstract:

The software evolution control requires a deep understanding of the changes and their impact on different system heterogeneous artifacts. And an understanding of descriptive knowledge of the developed software artifacts is a prerequisite condition for the success of the evolutionary process. The implementation of an evolutionary process is to make changes more or less important to many heterogeneous software artifacts such as source code, analysis and design models, unit testing, XML deployment descriptors, user guides, and others. These changes can be a source of degradation in functional, qualitative or behavioral terms of modified software. Hence the need for a unified approach for extraction and representation of different heterogeneous artifacts in order to ensure a unified and detailed description of heterogeneous software artifacts, exploitable by several software tools and allowing to responsible for the evolution of carry out the reasoning change concerned.

Keywords: Heterogeneous software artifacts, Software evolution control, Unified approach, Meta Model, Software Architecture.

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Authors: Chun-Der Chen, Yi-Wen Fan, Cheng-Kiang Farn

Abstract:

In today-s competitive global business environment, the concept of supply chain management (SCM) continues to become increasingly market-oriented, shifting the primary driver of the value chain from supply to demand. Recent recommendations encourage researchers to focus investigations on the supply chain process integration (SCPI) capabilities that integrate a focal firm with its network of suppliers and business customers to create value for it. However, theoretical and empirical researches pertaining to the antecedents and consequences of a focal firm-s SCPI capabilities have been limited and piecemeal. The purpose of this study is to investigate the critical determinants and consequences of a focal firm-s SCPI capabilities. We test our proposed research framework using a sample of 139 sales managers of manufacturing industries in Taiwan, our research findings show that (1) both perceived business customer-s power and focal firm-s market-oriented culture positively influences a focal firm-s SCPI capabilities, and (2) SCPI capabilities positively influence a focal firm-s SCM performance, both operational and strategic benefits. Implications for practitioners and researchers and suggestions for future research are also addressed in this study.

Keywords: Supply chain process integration capabilities, Perceived business customer's power, Market-oriented culture, Supply chain management performance.

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Authors: Laura Çami (Vorpsi), Xhon Skënderi

Abstract:

In today's rapidly evolving technological landscape, the traditional principles of contract law are facing significant challenges. The emergence of new technologies, such as electronic signatures, smart contracts, and online dispute resolution mechanisms, is transforming the way contracts are formed, interpreted, and enforced. This paper examines the implications of these technological advancements on the constitutional principles of contract law. One of the fundamental principles of contract law is freedom of contract, which ensures that parties have the autonomy to negotiate and enter into contracts as they see fit. However, the use of technology in the contracting process has the potential to disrupt this principle. For example, online platforms and marketplaces often offer standard-form contracts, which may not reflect the specific needs or interests of individual parties. This raises questions about the equality of bargaining power between parties and the extent to which parties are truly free to negotiate the terms of their contracts. Another important principle of contract law is the requirement of consideration, which requires that each party receives something of value in exchange for their promise. The use of digital assets, such as cryptocurrencies, has created new challenges in determining what constitutes valuable consideration in a contract. Due to the ambiguity in this area, disagreements about the legality and enforceability of such contracts may arise. Furthermore, the use of technology in dispute resolution mechanisms, such as online arbitration and mediation, may raise concerns about due process and access to justice. The use of algorithms and artificial intelligence to determine the outcome of disputes may also raise questions about the impartiality and fairness of the process. Finally, it should be noted that there are many different and complex effects of technical improvements on the fundamental constitutional foundations of contract law. As technology continues to evolve, it will be important for policymakers and legal practitioners to consider the potential impacts on contract law and to ensure that the principles of fairness, equality, and access to justice are preserved in the contracting process.

Keywords: Technological advancements, constitutional principles, contract law, smart contracts, online dispute resolution, freedom of contract.

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Authors: G. L. C. Yap

Abstract:

Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations.

Keywords: Long-memory, Gaussian process, Whittle estimator, normalization, volatility, value-at-risk.

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Authors: Shyam S.N. Perera

Abstract:

The optimal control problem for the viscoelastic melt spinning process has not been reported yet in the literature. In this study, an optimal control problem for a mathematical model of a viscoelastic melt spinning process is considered. Maxwell-Oldroyd model is used to describe the rheology of the polymeric material, the fiber is made of. The extrusion velocity of the polymer at the spinneret as well as the velocity and the temperature of the quench air and the fiber length serve as control variables. A constrained optimization problem is derived and the first–order optimality system is set up to obtain the adjoint equations. Numerical solutions are carried out using a steepest descent algorithm. A computer program in MATLAB is developed for simulations.

Keywords: Fiber spinning, Maxwell-Oldroyd, Optimal control, First-order optimality system, Adjoint system

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Authors: A. Sharahi, R. Tehrani, A. Mollajan

Abstract:

The final step to complete the “Analytical Systems Engineering Process” is the “Allocated Architecture” in which all Functional Requirements (FRs) of an engineering system must be allocated into their corresponding Physical Components (PCs). At this step, any design for developing the system’s allocated architecture in which no clear pattern of assigning the exclusive “responsibility” of each PC for fulfilling the allocated FR(s) can be found is considered a poor design that may cause difficulties in determining the specific PC(s) which has (have) failed to satisfy a given FR successfully. The present study utilizes the Axiomatic Design method principles to mathematically address this problem and establishes an “Axiomatic Model” as a solution for reaching good alternatives for developing the allocated architecture. This study proposes a “loss Function”, as a quantitative criterion to monetarily compare non-ideal designs for developing the allocated architecture and choose the one which imposes relatively lower cost to the system’s stakeholders. For the case-study, we use the existing design of U. S. electricity marketing subsystem, based on data provided by the U.S. Energy Information Administration (EIA). The result for 2012 shows the symptoms of a poor design and ineffectiveness due to coupling among the FRs of this subsystem.

Keywords: Allocated Architecture, Analytical Systems Engineering Process, Functional Requirements (FRs), Physical Components (PCs), Responsibility of a Physical Component, System’s Stakeholders.

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Authors: M. Anidha, K. Premalatha

Abstract:

Feature Selection is significant in order to perform constructive classification in the area of cancer diagnosis. However, a large number of features compared to the number of samples makes the task of classification computationally very hard and prone to errors in microarray gene expression datasets. In this paper, we present an innovative method for selecting highly informative gene subsets of gene expression data that effectively classifies the cancer data into tumorous and non-tumorous. The hybrid gene selection technique comprises of combined Mutual Information and Fisher score to select informative genes. The gene selection is validated by classification using Support Vector Machine (SVM) which is a supervised learning algorithm capable of solving complex classification problems. The results obtained from improved Mutual Information and F-Score with SVM as a classifier has produced efficient results.

Keywords: Gene selection, mutual information, Fisher score, classification, SVM.

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