Search results for: multiple objective programming

Authors: Zhang Xingnan, Huang Jingjia, Feng Yue, Burra Venkata Durga Kumar

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This paper proposes a comprehensive approach to mitigate ROP (Return-Oriented Programming) attacks by combining internal operating system protection mechanisms and hardware-assisted techniques. Through extensive literature review, we identify the effectiveness of ASLR (Address Space Layout Randomization) and LBR (Last Branch Record) in preventing ROP attacks. We present a process involving buffer overflow detection, hardware-assisted ROP attack detection, and the use of Turing detection technology to monitor control flow behavior. We envision a specialized tool that views and analyzes the last branch record, compares control flow with a baseline, and outputs differences in natural language. This tool offers a graphical interface, facilitating the prevention and detection of ROP attacks. The proposed approach and tool provide practical solutions for enhancing software security.

Keywords: operating system, ROP attacks, returning-oriented programming attacks, ASLR, LBR, CFI, DEP, code randomization, hardware-assisted CFI

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Authors: İsmail İnce, Mustafa Fener, Sair Kahraman

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The uniaxial compressive strength (UCS) of rocks is an important input parameter for the design of rock engineering project. Compressive strength can be determined in the laboratory using the uniaxial compressive strength (UCS) test. Although the test is relatively simple, the method is time consuming and expensive. Therefore many researchers have tried to assess the uniaxial compressive strength values of rocks via relatively simple and indirect tests (e.g. point load strength test, Schmidt Hammer hardness rebound test, P-wave velocity test, etc.). Pyroclastic rocks are widely exposed in the various regions of the world. Cappadocia region located in the Central Anatolia is one of the most spectacular cite of these regions. It is important to determine the mechanical behaviour of the pyroclastic rocks due to their ease of carving, heat insulation properties and building some civil engineering constructions in them. The purpose of this study is to estimate a widely varying uniaxial strength of pyroclastic rocks from Cappadocia region by means of point load strength, porosity, dry density and saturated density tests utilizing gene expression programming.

Keywords: pyroclastic rocks, uniaxial compressive strength, gene expression programming (GEP, Cappadocia region

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Authors: Abdullah Alsheddy

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This paper presents the employment of Pareto optimality as a strategy to help (single-objective) local search escaping local optima. Instead of local search, Pareto local search is applied to solve the quadratic assignment problem which is multi-objectivized by adding a helper objective. The additional objective is defined as a function of the primary one with augmented penalties that are dynamically updated.

Keywords: Pareto optimization, multi-objectivization, quadratic assignment problem, local search

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Authors: Xiang Li, Jian-Qiao Sun

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As the crucial component of city traffic network, intersections have significant impacts on urban traffic performance. Despite of the rapid development in transportation systems, increasing traffic volumes result in severe congestions especially at intersections in urban areas. Effective regulation of vehicle flows at intersections has always been an important issue in the traffic control system. This study presents a multi-objective optimization method at intersections with cellular automata to achieve better traffic performance. Vehicle conflicts and pedestrian interference are considered. Three categories of the traffic performance are studied including transportation efficiency, energy consumption and road safety. The left-turn signal type, signal timing and lane assignment are optimized for different traffic flows. The multi-objective optimization problem is solved with the cell mapping method. The optimization results show the conflicting nature of different traffic performance. The influence of different traffic variables on the intersection performance is investigated. It is observed that the proposed optimization method is effective in regulating the traffic at the intersection to meet multiple objectives. Transportation efficiency can be usually improved by the permissive left-turn signal, which sacrifices safety. Right-turn traffic suffers significantly when the right-turn lanes are shared with the through vehicles. The effect of vehicle flow on the intersection performance is significant. The display pattern of the optimization results can be changed remarkably by the traffic volume variation. Pedestrians have strong interference with the traffic system.

Keywords: cellular automata, intersection, multi-objective optimization, traffic system

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Authors: Gopinath Rathod, Vinod Puranik

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Sustainability is regarded as a key concept for survival in the competitive scenario. Industrial risk and diversification of risk type’s increases with industrial developments. In the context of sustainable manufacturing, the evaluation of risk is difficult because of the incomplete information and multiple indicators. Fuzzy Multiple Attribute Decision Method (FMADM) has been used with a three level hierarchical decision making model to evaluate aggregate risk for sustainable manufacturing projects. A case study has been presented to reflect the risk characteristics in sustainable manufacturing projects.

Keywords: sustainable manufacturing, decision making, aggregate risk, fuzzy logic, fuzzy multiple attribute decision method

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Authors: Peter M. Maurer Maurer

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DGL is a context free grammar-based tool for generating random data. Many types of simulator input data require some computation to be placed in the proper format. For example, it might be necessary to generate ordered triples in which the third element is the sum of the first two elements, or it might be necessary to generate random numbers in some sorted order. Although DGL is universal in computational power, generating these types of data is extremely difficult. To overcome this problem, we have enhanced DGL to include features that permit direct computation within the structure of a context free grammar. The features have been implemented as special types of productions, preserving the context free flavor of DGL specifications.

Keywords: DGL, Enhanced Context Free Grammars, Programming Constructs, Random Data Generation

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Authors: Osama Aziz, Hamza Ahmad, Muhibur Rahman

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The performance of wireless communication systems has been suggested to be improved by UWB MIMO antenna systems. However, creating a successful UWB MIMO antenna is a difficult undertaking that calls for resolving a number of design issues, including radiation efficiency, size, and frequency range. This study's primary objective is to create a novel, highly effective, small-sized, ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna and investigate its potential applications in body-centric communication. Two radiating elements, shared ground plane, circular stubs, and t-shaped isolation elements are used to achieve the MIMO antenna. Outstanding multiplexing efficiency, significant peak gain across the entire UWB frequency spectrum, extremely low mutual coupling (S21=-16 dB), high diversity gain (DG>9), and low envelop correlation are achieved. The proposed antenna will be one of the promising candidates for body centric communication.

Keywords: UWB communication, UWB MIMO antennas, body-centric communication, diversity gain

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Authors: Helga Martins, Idália Matias

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Background:Multiple sclerosis is a chronic inflammatory autoimmune demyelinating disease that affects young adults. Multiple sclerosis is a chronic disease in which the patient needs to self-manage the disease and the therapeutic regimen. Consequently, the promotion of health literacy assumes a relevant role for the accessibility, understanding, and use of information in order to promote and maintain the health of patients with multiple sclerosis. Aim: To determine the impact of lower health literacy in the self-management of patients with a multiple sclerosis. Methods: Literature review based on a search on the following electronic databases: CINAHLand MEDLINE; comprising all results published between September 2016 and September 2021. The search strategy was: (“Self-management [MeSH]” AND “Multiple sclerosis[MeSH]”AND “Health literacy[MeSH]”). The inclusion criteria were: original papers reporting about multiple sclerosis patients; participants with age above 18 years old, written in English, Spanish, French, or Portuguese. Two independent reviewers have done the screening and analysis of the results. 38 citations were identified, and after duplicates removal, a total of 25 results were screened; 14 were included after the application of the inclusion criteria. Results: The lower health literacy in the self-management of patients with a multiple sclerosis is related toless healthy choices, riskier health behavior, poor health outcomes, decreased of adhering to the therapeutic regimen after discharge, less self-management of chronic illness, and increased the time of hospitalization. Conclusion: Inadequate levels of health literacy contribute to poor health outcomes, unsuccessful self-management of chronic illness, and inadequate adherence to the therapeutic regimen. Therefore, health literacy is important for health policy and the healthcare services, as it can be understood as a mediator of self-management of multiple sclerosis disease.

Keywords: health literacy, multiple sclerosis, review, self-management

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Authors: Cem Isik Dogru, Salih Tekin, Kursad Derinkuyu

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Electric vehicle (EV) carsharing is an alternative method to tackle urban transportation problems. This method can be applied by several options. One of the options is the one-way carsharing, which allow an EV to be taken at a designated location and leaving it on another specified location customer desires. Although it may increase users’ satisfaction, the issues, namely, demand dissatisfaction, relocation of EVs and charging schedules, must be dealt with. Also, excessive electricity has to be stored in batteries of EVs. To cope with aforementioned issues, two-step mixed integer programming (MIP) model is proposed. In first step, the integer programming model is used to determine amount of electricity to be sold to the grid in terms of time periods for extra profit. Determined amounts are provided from the batteries of EVs. Also, this step works in day-ahead electricity markets with forecast of periodical electricity prices. In second step, other MIP model optimizes daily operations of one-way carsharing: charging-discharging schedules, relocation of EVs to serve more demand and renting to maximize the profit of EV fleet owner. Due to complexity of the models, heuristic methods are introduced to attain a feasible solution and different price information scenarios are compared.

Keywords: electric vehicles, forecasting, mixed integer programming, one-way carsharing

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Authors: Alireza Changizi, Arash Rezaei, Jamal Muhammad, Jyrki Latokartano, Minna Lanz

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Offline programming (OLP) is a new method in robot programming which is used widely in the industry nowadays which is a simulation base method that can produce the robot codes for motion according to virtual world in the simulation software. In this project Delmia v5 is used as simulation software. First the work cell component was modelled by Catia v5 and all of them was imported to a process file in Delmia and placed roughly to form the virtual work cell. Then robot was added to the work cell from the Delmia library. Work cell was calibrated corresponding to real world work cell to have accurate code. Tool calibration is the first step of calibration scheme and then work cell equipment can be calibrated using 6 point calibration method. Finally generated code needs to be reformed to match related controller code instruction. At the last stage IO were set to accomplish robots cooperation and make their motion synchronized. The pros and cons also will be discussed to clarify the presented results show the feasibility of the method and its effect on production line efficiency. Finally the positive and negative points of the implementation will be discussed.

Keywords: robotic, automated, production, offline programming, CAD

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Authors: Sarantos Psycharis

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Physical Computing, as an instructional model, is applied in the framework of the Engineering Pedagogy to teach “transversal/cross-cutting ideas” in a STEM content approach. Labview and Arduino were used in order to connect the physical world with real data in the framework of the so called Computational Experiment. Tertiary prospective engineering educators were engaged during their course and Computational Thinking (CT) concepts were registered before and after the intervention across didactic activities using validated questionnaires for the relationship between self-efficacy, computer programming, and CT concepts when STEM content epistemology is implemented in alignment with the Computational Pedagogy model. Results show a significant change in students’ responses for self-efficacy for CT before and after the instruction. Results also indicate a significant relation between the responses in the different CT concepts/practices. According to the findings, STEM content epistemology combined with Physical Computing should be a good candidate as a learning and teaching approach in university settings that enhances students’ engagement in CT concepts/practices.

Keywords: arduino, computational thinking, computer programming, Labview, self-efficacy, STEM

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Authors: Kang-Mo Jung

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Least squares support vector machine (LS-SVM) is a penalized regression which considers both fitting and generalization ability of a model. However, the squared loss function is very sensitive to even single outlier. We proposed a weighted absolute deviation loss function for the robustness of the estimates in least absolute deviation support vector machine. The proposed estimates can be obtained by a quadratic programming algorithm. Numerical experiments on simulated datasets show that the proposed algorithm is competitive in view of robustness to outliers.

Keywords: least absolute deviation, quadratic programming, robustness, support vector machine, weight

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Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

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Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

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Authors: Alime Cengiz, Talip Kahyaoglu

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Roasting process has the major importance to obtain desired aromatic taste of nuts. In this study, two kinds of roasting process were applied to hulled sesame seeds - vacuum oven and hot air roasting. Efficiency of Gene Expression Programming (GEP), a new soft computing technique of evolutionary algorithm that describes the cause and effect relationships in the data modelling system, and response surface methodology (RSM) were examined in the modelling of roasting processes over a range of temperature (120-180°C) for various times (30-60 min). Color attributes (L*, a*, b*, Browning Index (BI)), textural properties (hardness and fracturability) and moisture content were evaluated and modelled by RSM and GEP. The GEP-based formulations and RSM approach were compared with experimental results and evaluated according to correlation coefficients. The results showed that both GEP and RSM were found to be able to adequately learn the relation between roasting conditions and physical and textural parameters of roasted seeds. However, GEP had better prediction performance than the RSM with the high correlation coefficients (R2 >0.92) for the all quality parameters. This result indicates that the soft computing techniques have better capability for describing the physical changes occuring in sesame seeds during roasting process.

Keywords: genetic expression programming, response surface methodology, roasting, sesame seed

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Authors: Hao-Wei Fu, Chung-Feng Kao

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In the era of rapid technological advancement, information technology (IT) has become integral to modern life, exerting significant influence across diverse sectors and serving as a catalyst for development in various industries. Within agriculture, the integration of IT offers substantial benefits, notably enhancing operational efficiency. Real-time monitoring systems, for instance, have been widely embraced in agriculture, effectively improving crop management practices. This study specifically addresses the management of rice panicle fertilizer, presenting the development of a web application tailored to handle data associated with rice panicle fertilizer management. Leveraging the normalized difference red edge index, this application optimizes the quantity of rice panicle fertilizer used, providing recommendations to agricultural stakeholders and service providers in the agricultural information sector. The overarching objective is to minimize costs while maximizing yields. Furthermore, a robust database system has been established to store and manage relevant data for future reference in rice cultivation management. Additionally, the study utilizes the Representational State Transfer software architectural style to construct an application programming interface (API), facilitating data creation, retrieval, updating, and deletion for users via the HyperText Transfer Protocol methods. Future plans involve integrating this API with third-party services to incorporate it into larger frameworks, thus catering to the diverse requirements of various third-party services.

Keywords: application programming interface, HyperText Transfer Protocol, nitrogen fertilizer intelligent management, web-based application

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Authors: Trupti Diwan

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Predicting student failure at school has changed into a difficult challenge due to both the large number of factors that can affect the reduced performance of students and the imbalanced nature of these kinds of data sets. This paper surveys the two elements needed to make prediction on Students’ Academic Performances which are parameters and methods. This paper also proposes a framework for predicting the performance of engineering students. Genetic programming can be used to predict student failure/success. Ranking algorithm is used to rank students according to their credit points. The framework can be used as a basis for the system implementation & prediction of students’ Academic Performance in Higher Learning Institute.

Keywords: classification, educational data mining, student failure, grammar-based genetic programming

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Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

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It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

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Authors: Srivatsav Sanjay Sridhar, Asvitha Raja, Prathit Kalra, Soni Gupta

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Database management is a system that keeps track of details about a person in an organisation. Not a lot of orphanages these days are shifting to a computer and program-based system, but unfortunately, most have only pen and paper-based records, which not only consumes space but it is also not eco-friendly. It comes as a hassle when one has to view a record of a person as they have to search through multiple records, and it will consume time. This program will organise all the data and can pull out any information about anyone whose data is entered. This is also a safe way of storage as physical data gets degraded over time or, worse, destroyed due to natural disasters. In this developing world, it is only smart enough to shift all data to an electronic-based storage system. The program comes with all features, including creating, inserting, searching, and deleting the data, as well as printing them.

Keywords: database, orphans, programming, C⁺⁺

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Authors: Muzammil Dar

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The confluence of trans-national interests and divergent approaches followed by multiple actors has surrounded the Indo-Pacific region with myriad of strategic complexes- Geo-Political, Geo-economic, and security. This paper has thus made a humble attempt to understand the Indo-Pacific strategic predicament from Asia-Pacific perspective. The portmanteau of Indo-Pacific strategic gamble has multiple actors from global powers to regional actors. On the indo-pacific waters, not only flow trade relations, but the tides of conflicts and controversies are striking these actors against each other. The alliance formation and infrastructure building has built-in threat perceptions from rivals vice-versa. The assertiveness of China as a reality and India’s ideological doctrine of peace and friendship, as well as American rebalancing against China, could be seen as clear and bright on the Indo-Pacific strategic portmanteau. ASEAN and Japan, too, have oscillating posturing in the strategic dilemma. The aim and objective of the paper are to sketch out the prospectus and prejudices of Indo-pacific strategic complex.

Keywords: Indo Pacific, Asia Pacific, security and growth for all in the region, SAGAR, ASEAN China

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Authors: Ali Mohammadi

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Every construction that is done, the most important part of attention for employers and contractors is its cost, and they always try to reduce costs so that they can compete in the market, so they estimate the cost of construction before starting their activities. The costs can be generally divided into four parts: the materials used, the equipment used, the manpower required, and the time required. In this article, we are trying to talk about the three items of equipment, manpower, and time, and examine how the use of apps can reduce the cost of construction, while due to various reasons, it has received less attention in the field of app design. Also, because we intend to use these apps in construction and they are used by engineers and experts, we define these apps as engineering apps because the idea of ​​their design must be by an engineer who works in that field. Also, considering that most engineers are familiar with programming during their studies, they can design the apps they need using simple programming software.

Keywords: layout, as-bilt, monitoring, maps

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Authors: Sukhveer Singh, Sandeep Singh

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A bi-objective fuzzy transportation problem with the objectives to minimize the total fuzzy cost and fuzzy time of transportation without according priorities to them is considered. To the best of our knowledge, there is no method in the literature to find efficient solutions of the bi-objective transportation problem under uncertainty. In this paper, a bi-objective transportation problem in an uncertain environment has been formulated. An algorithm has been proposed to find efficient solutions of the bi-objective transportation problem under uncertainty. The proposed algorithm avoids the degeneracy and gives the optimal solution faster than other existing algorithms for the given uncertain transportation problem.

Keywords: uncertain transportation problem, efficient solution, ranking function, fuzzy transportation problem

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Authors: Weizhi Zhong, Xiaoyi Lu, Lei Xu

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In order to solve the problem of inaccurate synchronization for distributed multiple-input multiple-output (MIMO) system in multipath environment, a golay pair aided timing synchronization method is proposed in this paper. A new synchronous training sequence based on golay pair is designed. By utilizing the aperiodic auto-correlation complementary property of the new training sequence, the fine timing point is obtained at the receiver. Simulation results show that, compared with the tradition timing synchronization approaches, the proposed algorithm can provide high accuracy in synchronization, especially under multipath condition.

Keywords: distributed MIMO system, golay pair, multipath, synchronization

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Authors: Alireza Nikbakht Shahbazi, Emadeddin Shirali

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Since optimization issues of water resources are complicated due to the variety of decision making criteria and objective functions, it is sometimes impossible to resolve them through regular optimization methods or, it is time or money consuming. Therefore, the use of modern tools and methods is inevitable in resolving such problems. An accurate and essential utilization policy has to be determined in order to use natural resources such as water reservoirs optimally. Water reservoir programming studies aim to determine the final cultivated land area based on predefined agricultural models and water requirements. Dam utilization rule curve is also provided in such studies. The basic information applied in water reservoir programming studies generally include meteorological, hydrological, agricultural and water reservoir related data, and the geometric characteristics of the reservoir. The system of Dez dam water resources was simulated applying the basic information in order to determine the capability of its reservoir to provide the objectives of the performed plan. As a meta-exploratory method, genetic algorithm was applied in order to provide utilization rule curves (intersecting the reservoir volume). MATLAB software was used in order to resolve the foresaid model. Rule curves were firstly obtained through genetic algorithm. Then the significance of using rule curves and the decrease in decision making variables in the system was determined through system simulation and comparing the results with optimization results (Standard Operating Procedure). One of the most essential issues in optimization of a complicated water resource system is the increasing number of variables. Therefore a lot of time is required to find an optimum answer and in some cases, no desirable result is obtained. In this research, intersecting the reservoir volume has been applied as a modern model in order to reduce the number of variables. Water reservoir programming studies has been performed based on basic information, general hypotheses and standards and applying monthly simulation technique for a statistical period of 30 years. Results indicated that application of rule curve prevents the extreme shortages and decrease the monthly shortages.

Keywords: optimization, rule curve, genetic algorithm method, Dez dam reservoir

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Authors: Ofole Ndidi

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Context: Empirical studies show that through dual primary attachment mothers and fathers contribute to children’s development and behaviours. While the contribution of mothers is well documented in past researches, fathers’ involvement in Nigeria has received much less attention. As such, exploring fathers’ involvement in sexual behaviours will provide insight for policy implementation and programming designed to delay sexual debut among sexually inexperienced young people in Nigeria. Objective of study: This study examined the extent to which father involvement (father’s parenting style, attitude, father-child communication, father’s marital status, and father’s socio-economic status) could predict delay in sexual debut of a representative sample of Nigeria adolescents in lower secondary. Materials and Methods: Multistage sampling technique was adopted to draw a cross section of 1023 adolescents with the age range of 10-23 years and mean years of 12±2.1 who reported sexually inexperience from six geographical zones in Nigeria. Multiple Regressions was used to analyze the data collected with four standardized self-report measures at 0.05 level of significance. Results: Findings of this study revealed that the independent variables (father’s parenting style, paternal attitudes, paternal–child communication, paternal marital status and paternal socio–economic status) contributed significantly to the delay of sexual debut. However, fathers’ attitude made the most potent contribution (β = 0.255, P < 0.05). Conclusions: The outcomes of this study have implications for programs that are designed to reduce high-risk behaviors among adolescents. It concluded that sexuality education and interventions should involve the fathers in a more integrated and collaborative fashion.

Keywords: father, sexual debut, adolescents, Nigeria

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Authors: K. -H. Yang

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Supplier selection problem is one of the important issues of supply chain problems. Two categories of methodologies include qualitative and quantitative approaches which can be applied to supplier selection problems. However, due to the complexities of the problem and lacking of reliable and quantitative data, qualitative approaches are more than quantitative approaches. This study considers operational cost and supplier’s reliability factor and solves the problem by using a quantitative approach. A mixed integer programming model is the primary analytic tool. Analyses of different scenarios with variable cost and reliability structures show that the effectiveness of this approach to the supplier selection problem.

Keywords: mixed integer programming, quantitative approach, supplier’s reliability, supplier selection

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Authors: Genady Grabarnik, Serge Yaskolko

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Generative Artificial Intelligence (AI) has significantly expanded its applicability with the incorporation of Large Language Models (LLMs) and become a technology with promise to automate some areas that were very difficult to automate before. The paper describes the introduction of generative Artificial Intelligence into Introductory Computer and Data Science courses and analysis of effect of such introduction. The generative Artificial Intelligence is incorporated in the educational process two-fold: For the instructors, we create templates of prompts for generation of tasks, and grading of the students work, including feedback on the submitted assignments. For the students, we introduce them to basic prompt engineering, which in turn will be used for generation of test cases based on description of the problems, generating code snippets for the single block complexity programming, and partitioning into such blocks of an average size complexity programming. The above-mentioned classes are run using Large Language Models, and feedback from instructors and students and courses’ outcomes are collected. The analysis shows statistically significant positive effect and preference of both stakeholders.

Keywords: introductory computer and data science education, generative AI, large language models, application of LLMS to computer and data science education

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Authors: Amirhossein Khazali, Mohsen Kalantar

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Energy storage units can play an important role to provide an economic and secure operation of future energy systems. In this paper, a stochastic energy and reserve market clearing scheme is presented considering storage energy units. The approach is proposed to deal with stochastic and non-dispatchable renewable sources with a high level of penetration in the energy system. A two stage stochastic programming scheme is formulated where in the first stage the energy market is cleared according to the forecasted amount of wind generation and demands and in the second stage the real time market is solved according to the assumed scenarios.

Keywords: energy and reserve market, energy storage device, stochastic programming, wind generation

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Authors: Min Dai, Hong Liu, Shuaijie Qian

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We study a portfolio selection problem of an investor who faces constraints on rebalancing frequency, which is common in pension fund investment. We formulate it as a multiple optimal stopping problem and utilize the dynamic programming principle. By numerically solving the corresponding Hamilton-Jacobi-Bellman (HJB) equation, we find a series of free boundaries characterizing optimal strategy, and the constraints significantly impact the optimal strategy. Even in the absence of transaction costs, there is a no-trading region, depending on the number of the remaining trading chances. We also find that the equivalent wealth loss caused by the constraints is large. In conclusion, our model clarifies the impact of the constraints on transaction frequency on the optimal strategy.

Keywords: portfolio selection, rebalancing frequency, optimal strategy, free boundary, optimal stopping

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Authors: Chen Guo, Heng Tang, Ben Niu

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Clustering splits objects into different groups based on similarity, making the objects have higher similarity in the same group and lower similarity in different groups. Thus, clustering can be treated as an optimization problem to maximize the intra-cluster similarity or inter-cluster dissimilarity. In real-world applications, the datasets often have some complex characteristics: sparse, overlap, high dimensionality, etc. When facing these datasets, simultaneously optimizing two or more objectives can obtain better clustering results than optimizing one objective. However, except for the objectives weighting methods, traditional clustering approaches have difficulty in solving multi-objective data clustering problems. Due to this, evolutionary multi-objective optimization algorithms are investigated by researchers to optimize multiple clustering objectives. In this paper, the Data Clustering algorithm based on Multi-objective Periodic Bacterial Foraging Optimization with two Learning Archives (DC-MPBFOLA) is proposed. Specifically, first, to reduce the high computing complexity of the original BFO, periodic BFO is employed as the basic algorithmic framework. Then transfer the periodic BFO into a multi-objective type. Second, two learning strategies are proposed based on the two learning archives to guide the bacterial swarm to move in a better direction. On the one hand, the global best is selected from the global learning archive according to the convergence index and diversity index. On the other hand, the personal best is selected from the personal learning archive according to the sum of weighted objectives. According to the aforementioned learning strategies, a chemotaxis operation is designed. Third, an elite learning strategy is designed to provide fresh power to the objects in two learning archives. When the objects in these two archives do not change for two consecutive times, randomly initializing one dimension of objects can prevent the proposed algorithm from falling into local optima. Fourth, to validate the performance of the proposed algorithm, DC-MPBFOLA is compared with four state-of-art evolutionary multi-objective optimization algorithms and one classical clustering algorithm on evaluation indexes of datasets. To further verify the effectiveness and feasibility of designed strategies in DC-MPBFOLA, variants of DC-MPBFOLA are also proposed. Experimental results demonstrate that DC-MPBFOLA outperforms its competitors regarding all evaluation indexes and clustering partitions. These results also indicate that the designed strategies positively influence the performance improvement of the original BFO.

Keywords: data clustering, multi-objective optimization, bacterial foraging optimization, learning archives

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Authors: Bualak Naksongkaew

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The purposes of this study were to compare pre- and post-test achievement of Thai language skills. The samples consisted of 40 tenth grader of Secondary Demonstration School of Suan Sunandha Rajabhat University in the first semester of the academic year 2010. The researcher prepared the Thai lesson plans, the pre- and post-achievement test at the end program. Data analyses were carried out using means, standard deviations and descriptive statistics, independent samples t-test analysis for comparison pre- and post-test. The study showed that there were a statistically significant difference at α= 0.05; therefore the use multiple intelligences theory can develop Thai languages skills. The results after using the multiple intelligences theory for Thai lessons had higher level than standard.

Keywords: multiple intelligences theory, Thai language skills, development, pre- and post-test achievement

Procedia PDF Downloads 398