Finite-Time Sideslip Differentiator-Based LOS Guidance for Robust Path Following of Snake Robots

This paper presents a finite-time sideslip differentiator-based line-of-sight(LOS)guidance method for robust path following of snake robots.Firstly,finite-time stable sideslip differentiator and adaptive LOS guidance method are proposed to counteract sideslip drift caused by cross-track velocity.The proposed differentiator can accurately observe the cross-track error and sideslip angle for snake robots to avoid errors caused by calculating sideslip angle approximately.In our method,the designed piecewise auxiliary function guarantees the finite-time stability of position errors.Secondly,for the case of external disturbances and state constraints,a Barrier Lyapunov functionbased backstepping adaptive path following controller is presented to improve the robot’s robustness.The uniform ultimate boundedness of the closed-loop system is proved by analyzing stability.Additionally,a gait frequency adjustment-based virtual velocity control input is derived to achieve the exponential convergence of the tangential velocity.At last,the availability and superiority of this work are shown through simulation and experiment results.

Energy Consumption Analysis and Characterization of Aerospace Manufacturing Facilities in the United States–A Step towards Sustainable Development

In this study,information on energy usage in the United States(U.S.)aerospace manufacturing sector has been analyzed and then represented as energy intensities(kWh/m2)to establish benchmark data and to compare facilities of varying sizes.First,public sources were identified and the data from these previously published sources were aggregated to determine the energy usage of aerospace manufacturing facilities within the U.S.From this dataset,a sample of 28 buildings were selected and the energy intensity for each building was estimated from the data.Next,as a part of this study the energy data for three additional aerospace manufacturing facilities in the U.S.were collected firsthand.That data was analyzed and the energy intensity(kWh/m2)for each facility was calculated and then compared with the energy intensities of the 28 buildings from the sample.Three different indicators of energy consumption in aerospace manufacturing facilities were used as comparators to assist facility managers with determining potential energy savings and help in the decision-making process.On average,aerospace manufacturing facilities in the United States spent 4 cents for each dollar of sale on energy.The energy intensity(kWh/m2)and the power intensity(W/m2)for each facility were calculated based on the actual facility energy bills.The power intensity for these facilities ranges from 34 to 134 W/m2.The energy intensity ranged from 232 to 949 kWh/m2.We found that the power intensity could be used to estimate energy consumption when the annual operating hours of the facility are considered.and to estimate the energy-related carbon dioxide emissions.

Unmanned Aerial Vehicle Inspection Routing and Scheduling for Engineering Management

Technological advancements in unmanned aerial vehicles(UAVs)have revolutionized various industries,enabling the widespread adoption of UAV-based solutions.In engineering management,UAV-based inspection has emerged as a highly efficient method for identifying hidden risks in high-risk construction environments,surpassing traditional inspection techniques.Building on this foundation,this paper delves into the optimization of UAV inspection routing and scheduling,addressing the complexity introduced by factors such as no-fly zones,monitoring-interval time windows,and multiple monitoring rounds.To tackle this challenging problem,we propose a mixed-integer linear programming(MILP)model that optimizes inspection task assignments,monitoring sequence schedules,and charging decisions.The comprehensive consideration of these factors differentiates our problem from conventional vehicle routing problem(VRP),leading to a mathematically intractable model for commercial solvers in the case of large-scale instances.To overcome this limitation,we design a tailored variable neighborhood search(VNS)metaheuristic,customizing the algorithm to efficiently solve our model.Extensive numerical experiments are conducted to validate the efficacy of our proposed algorithm,demonstrating its scalability for both large-scale and real-scale instances.Sensitivity experiments and a case study based on an actual engineering project are also conducted,providing valuable insights for engineering managers to enhance inspection work efficiency.

Spatial effect of environmental regulation measures on industrial structure upgrading from the empirical analysis of Beijing-Tianjin-Hebei region and its surrounding areas

This paper investigates the spatial effect of environmental regulation measures on the upgrading of industrial structure in the integrated development strategy of Beijing-Tianjin-Hebei region and its surrounding areas.In order to reflect the effect of the environmental regulation and different regulation measures more truly,this paper constructs indices of the environmental regulation measures through the results of policy texts quantification.On the basis of the previous research,this paper divides environmental regulation into the following types:personnel and administrative measures of command and control;market-oriented fiscal,taxation,financial and other economic measures;guidance measures.Spatial panel regression results show that administrative measures of command control and market-oriented fiscal measures have a significant role in promoting regional industrial structure upgrading,but not conducive to the advancement of the industrial structure of adjacent areas.Their roles in promoting and inhibition are counteracted,which causes the total effect of industrial structure upgrading of Beijing-Tianjin-Hebei and the surrounding areas are not significant.Personnel measures,financial measures,other economic measures and guidance measures do not have the short-term effect and spatial effect on the upgrading of industrial structure.

MELex: The Construction of Malay-English Sentiment Lexicon

Currently,the sentiment analysis research in the Malaysian context lacks in terms of the availability of the sentiment lexicon.Thus,this issue is addressed in this paper in order to enhance the accuracy of sentiment analysis.In this study,a new lexicon for sentiment analysis is constructed.A detailed review of existing approaches has been conducted,and a new bilingual sentiment lexicon known as MELex(Malay-English Lexicon)has been generated.Constructing MELex involves three activities:seed words selection,polarity assignment,and synonym expansions.Our approach differs from previous works in that MELex can analyze text for the two most widely used languages in Malaysia,Malay,and English,with the accuracy achieved,is 90%.It is evaluated based on the experimentation and case study approaches where the affordable housing projects in Malaysia are selected as case projects.This finding has given an implication on the ability of MELex to analyze public sentiments in the Malaysian context.The novel aspects of this paper are two-fold.Firstly,it introduces the new technique in assigning the polarity score,and second,it improves the performance over the classification of mixed language content.

Evaluation of Infiltration Capacity and Water Retention Potential of Amended Soil Using Bamboo Charcoal and Humus for Urban Flood Prevention

In Japan, floods occur frequently in urban areas because non-infiltrating areas are seeing increased urbanization. To prevent floods, urban basins must improve the infiltration capacity and water retention of the whole basin. There are several basic technologies for river basin management, such as infiltration trenches or rainwater storage. However, a method of soil amendment that prevents flood disasters has not been established. This study aims to evaluate the infiltration capacity of soil amendments using bamboo charcoal and humus. A constant-head infiltration test and rainfall simulation were conducted to evaluate the properties of the soil amendments. The constant-head infiltration test＇s results showed that soils mixed with 30% humus had the greatest potential for influencing initial and final infiltration rates, and the more the mixing rates of bamboo charcoal and humus were increased, the higher the water retention capacity. The results of the rainfall simulation showed that soils mixed with 30% humus had the highest final infiltration rates and lowest multiplication spillage. To reduce the runoff volume using soil amendment technology, it is important to delay overland flow, and the hydraulic properties of the soils mixed with bamboo charcoal and humus were as effective as those of granite soils.

A Decision Aid Approach for Optimisation Problems Involving Several Economic Functions

Many concrete real life problems ranging from economic and business to industrial and engineering may be cast into a multi-objective optimisation framework. The redundancy of existing methods for solving this kind of problems susceptible to inconsistencies, coupled with the necessity for checking inherent assumptions before using a given method, make it hard for a nonspecialist to choose a method that fits well the situation at hand. Moreover, using blindly a method as proponents of the hammer principle (when you only have a hammer, you want everything in your hand to be a nail) is an awkward approach at best and a caricatural one at worst. This brings challenges to the design of a tool able to help a Decision Maker faced with these kinds of problems. The help should be at two levels. First the tool should be able to choose an appropriate multi-objective programming technique and second it should single out a satisfying solution using the chosen technique. The choice of a method should be made according to the structure of the problem and to the Decision Maker’s judgment value. This paper is an attempt to satisfy that need. We present a Decision Aid Approach that embeds a sample of good multi-objective programming techniques. The system is able to assist the Decision Maker in the above mentioned two tasks.

Tanaka Formula and Local Time for a Class of Interacting Branching Measure-valued Diffusions

We construct superprocesses with dependent spatial motion(SDSMs)in Euclidean spaces R^(d)with d≥1 and show that,even when they start at some unbounded initial positive Radon measure such as Lebesgue measure on R^(d),their local times exist when d≤3.A Tanaka formula of the local time is also derived.

Sustainable food waste management using modified fuzzy improved analytic hierarchy process:a study of Malaysia

Food waste generation is a pressing issue that requires urgent attention and concerted efforts worldwide.The staggering amount of food wasted each year not only wastes valuable resources but also exacerbates environmental,economic,and social challenges.Food Waste Management(FWM)consists of a complex array of criteria and sub-criteria,and treatments which seems interdependent.There is a need to evaluate the FWM with the help of important criteria and sub-criteria and treatments to address this challenge.In this study,we identified four important criteria,21 sub-criteria,and four alternatives of FWM for the case of Malaysia using the integrated approach of literature review and expert opinions.Further,we employed the approach of Modified Fuzzy Improved Analytical Hierarchy Process(IAHP)to corroborate the interrelationships among the identified criteria and sub-criteria,and their associated treatments.This study undertakes linear normalization methods to transform data into comparable numerical values and the Geometric Mean method to handle uncertainty in human judgments.Moreover,the Centroid method is employed to convert fuzzy weights into crisp sets for ease of interpretation.The results indicate that environmental is the most essential criterion,followed by social,economic,and technical.In addition,air and water pollution is identified as the most critical sub-criteria.Black Soldier Fly is discovered as the most sustainable FWM treatment,since it performs the best while meeting all the criteria and sub-criteria assessed.Sensitivity analysis demonstrates that the outputs from the proposed method are robust and reliable.The finding suggests a proper and robust approach to help decision-makers select suitable FWM treatments to tackle various criteria and alternatives especially when handling inconsistent and uncertain judgments during evaluation.

Chance-Constrained Approaches for Multiobjective Stochastic Linear Programming Problems

Multiple objective stochastic linear programming is a relevant topic. As a matter of fact, many practical problems ranging from portfolio selection to water resource management may be cast into this framework. Severe limitations on objectivity are encountered in this field because of the simultaneous presence of randomness and conflicting goals. In such a turbulent environment, the mainstay of rational choice cannot hold and it is virtually impossible to provide a truly scientific foundation for an optimal decision. In this paper, we resort to the bounded rationality principle to introduce satisfying solution for multiobjective stochastic linear programming problems. These solutions that are based on the chance-constrained paradigm are characterized under the assumption of normality of involved random variables. Ways for singling out such solutions are also discussed and a numerical example provided for the sake of illustration.

ANALYSIS OF FREEMIUM BUSINESS MODEL CONSIDERING NETWORK EXTERNALITIES AND CONSUMER UNCERTAINTY

An emerging business model increasingly used by companies in the online software market is to provide both a free basic version and a paid premium version for a service or a product to customers. Such a setting is often called freemium model. The existence of the free version can reduce the customer uncertainty regarding the evaluation of the commercial software and make use of network effect to improve the firm＇s profit. However, the freemium model may also have the cannibalization effect which can hurt the profit. Hence, the from needs to determine the optimal content for the free version and the optimal price for the premium version to maximize its profit. In this paper, thst, we obtain the optimal decisions of the freemium model and their properties. Second, we compare the freemium model with the traditional charge-for-everything model that all content of the product need to be charged in terms of the profit, customer welfare, and social welfare. The results show that when customer underestimates the value of the software significantly and the true value of the software is high enough, the freemium model can generate higher profit, higher customer welfare, and higher social welfare. Otherwise, the freemium model may not deliver the desired results.

Structural analysis and forecast of gold price returns

Gold has multiple attributes and its price is affected by various factors in the market.This paper studies the dynamic relationship between the gold price returns and its affecting factors.Then we use the STL-ETS,neural network and Bayesian structural time series model to predict the gold price returns,and compare their performance with the benchmark models.The results show that the shocks of crude oil returns and VIX have the positive effect on gold price returns,the shocks of the US dollar index have the negative effect on gold price returns.And the fluctuation of gold price returns mainly depends on crude oil price returns shocks.STL-ETS model can accurately fit the fluctuation trend of the gold price returns and improve prediction accuracy.

MMPP/M/C queue with congestion-based staffing policy and applications in operations of steel industry

A queueing model of the Markov-modulated Poisson process (MMPP) with thresholds was investigated. The customer arrival with various arrival rates in the model was viewed as the MMPP. In contrast to the Poisson, s arrival process, the MMPP can better describe the situation that the arrival rate changes with changing conditions;therefore, the model fits better with reality. The threshold conversion was added to the model based on the general MMPP/M/C model. When the number of customers in the system exceeds a threshold, all servers work to serve;when the number of customers in the system is less than another threshold, some servers are shut down. This is the congestion-based staffing policy with two thresholds. Specifically, the problems in the slab stocking stage of slab production at the Iron and Steel Complex in China were analysed. In the slab production process, because the rate of the upstream steelmaking is not constant, the rate of slab reaching the slab yard is uncertain. The crane service is used to store slabs in a warehouse. Because the slab arrival rate varies, different numbers of cranes in service need to be optimized for cost control. Thus, MMPP was used to describe slab arrival with varied arrival rates. Therefore, an MMPP/M/C queue with thresholds was used to analyse and solve the practical problems, and the optimal number of service cranes was obtained to minimize the cost of slab stocking.

Modeling optimal long-term investment strategies of hybrid wind-thermal companies in restructured power market

In this paper,a novel framework for the estimation of optimal investment strategies for combined wind-thermal companies is proposed.The medium-term restructured power market was simulated by considering the stochastic and rational uncertainties,the wind uncertainty was evaluated based on a data mining technique,and the electricity demand and fuel price were simulated using the Monte Carlo method.The Cournot game concept was used to determine the Nash equilibrium for each state and stage of the stochastic dynamic programming(DP).Furthermore,the long-term stochastic uncertainties were modeled based on the Markov chain process.The longterm optimal investment strategies were then solved for combined wind-thermal investors based on the semi-definite programming(SDP)technique.Finally,the proposed framework was implemented in the hypothetical restructured power market using the IEEE reliability test system(RTS).The conducted case study confirmed that this framework provides robust decisions and precise information about the restructured power market for combined wind-thermal investors.

Hierarchical modeling of stochastic manufacturing and service systems

This paper presents a review of methodologies for analyzing stochastic manufacturing and service systems. On the basis of the scale and level of details of operations, we can study stochastic systems using micro-,meso-, and macro-scopic models. Such a classification unifies stochastic modeling theory. For each model type,we highlight the advantages and disadvantages and the applicable situations. Micro-scopic models are based on quasi-birth-and-death process because of the phase-type distributed service times and/or Markov arrival processes.Such models are appropriate for modeling the detailed operations of a manufacturing system with relatively small number of servers(production facilities). By contrast,meso-scopic and macro-scopic models are based on the functional central limit theorem(FCLT) and functional strong law of large numbers(FSLLN), respectively, under heavy-traffic regimes. These high-level models are appropriate for modeling large-scale service systems with many servers, such as call centers or large service networks. This review will help practitioners select the appropriate level of modeling to enhance their understanding of the dynamic behavior of manufacturing or service systems. Enhanced understanding will ensure that optimal policies can be designed to improve system performance. Researchers in operation analytics and optimization of manufacturing and logistics also benefit from such a review.

Integrating operations research into green logistics:A review

Logistical activities have a significant global environmental impact,necessitating the adoption of green logistics practices to mitigate environmental effects.The COVID-19 pandemic has further emphasized the urgency to address the environmental crisis.Operations research provides a means to balance environmental concerns and costs,thereby enhancing the management of logistical activities.This paper presents a comprehensive review of studies integrating operations research into green logistics.A systematic search was conducted in the Web of Science Core Collection database,covering papers published until June 3,2023.Six keywords(green logistics OR sustainable logistics OR cleaner logistics OR green transportation OR sustainable transportation OR cleaner transportation)were used to identify relevant papers.The reviewed studies were categorized into five main research directions:Green waste logistics,the impact of costs on green logistics,the green routing problem,green transport network design,and emerging challenges in green logistics.The review concludes by outlining suggestions for further research that combines green logistics and operations research,with particular emphasis on investigating the long-term effects of the pandemic on this field.

A CASE FOR SERVICE SYSTEMS ENGINEERING

A case is made for further developing a branch of systems engineering that focuses on problems and issues which arise in the service sector. We promulgate this special focus not only because of the size and importance of the service sector but also because of the unique opportunities that systems engineering can exploit in the design and joint production and delivery of services. We begin by considering the economic, technological and demographic contexts within which the service sector has flourished; we then address both services, especially emerging services, and systems engineering, followed by a discussion of how to advance the field of service systems engineering, and concluding with several remarks. In particular, a number of service systems engineering methods are identified to enhance the design and production/delivery of services, especially taking advantage of the unique features that characterize services - namely, services, especially emerging services, are information-driven, customer-centric, e-oriented, and productivity-focused.

A CALCULUS FOR SERVICES INNOVATION

Innovation in the services area - especially in the electronic services （e-services） domain - can be systematically developed by first considering the strategic drivers and foci, then the tactical principles and enablers, and finally the operational decision attributes, all of which constitute a process or calculus of services innovation. More specifically, there are four customer drivers （i.e., collaboration, customization, integration and adaptation）, three business foci （i.e., creation-focused, solution-focused and competition-focused）, six business principles （i.e., reconstruct market boundaries, focus on the big picture not numbers, reach beyond existing demand, get strategic sequence right, overcome organizational hurdles and build execution into strategy）, eight technical enablers （i.e., software algorithms, automation, telecommunication, collaboration, standardization, customization, organization, and globalization）, and six attributes of decision informatics （i.e., decision-driven, information-based, real-time, continuously-adaptive, customer-centric and computationally-intensive）. It should be noted that the four customer drivers are all directed at empowering the individual - that is, at recognizing that the individual can, respectively, contribute in a collaborative situation, receive customized or personalized attention, access an integrated system or process, and obtain adaptive real-time or just-in-time input. The developed process or calculus serves to identify the potential white spaces or blue oceans for innovation. In addition to expanding on current innovations in services and related experiences, white spaces are identified for possible future innovations; they include those that can mitigate the unforeseen consequences or abuses of earlier innovations, safeguard our rights to privacy, protect us from the always-on, interconnected world, provide us with an authoritative search engine, and generate a GDP metric that can adequately measure the growing knowledge economy, one driven by intangible ideas and services innovation.

ON SERVICES RESEARCH AND EDUCATION

The importance of the services sector can not be overstated; it employs 82.1 percent of the U. S. workforce and 69 percent of graduates from an example technological university. Yet, university research and education have not followed suit. Clearly, services research and education deserve our critical attention and support since services - and services innovation - serve as an indispensable engine for global economic growth. The theme of this paper is that we can and should build services research and education on what has occurred in manufacturing research （especially in regard to customization and intellectual property） and education; indeed, services and manufactured goods become indistinguishable as they are jointly co-produced in real-time. Fortunately, inasmuch as manufacturing concepts, methodologies and technologies have been developed and refined over a long period of time （i.e., since the 1800s）, the complementary set of concepts, methodologies and technologies for services are more obvious. However, while new technologies （e.g., the Internet） and globalization trends have served to enable, if not facilitate, services innovation, the same technologies （e.g., the Internet） and 21st Century realities （e.g., terrorism） are making services innovation a far more complex problem and, in fact, may be undermining previous innovations in both services and manufacturing. Finally, there is a need to define a ＂knowledge-adjusted＂ GDP metric that can more adequately measure the growing knowledge economy, one driven by intangible ideas and services innovation.

CONSUMER-DRIVEN GROUP BUYING： TRICK OR TREAT TO RETAIL STORES？

Group buying （GB） has emerged and evolved into various forms over the past decade. We investigate a distinct form of GB, namely consumer-driven group buying, whereby some consumers form purchase groups to visit stores together and negotiate for discounts. We refer to these consumers as GB consumers that differ from regular consumers who visit stores individually and pay regular prices. Visited by a purchase group, a store has to make an immediate decision to serve their demand in its entirety. Turned down by the first store it visits, the purchase group continues to visit the other store. After accommodating GB demand, the stores use remaining stocks to serve regular consumers. We demonstrate that GB can be a treat to stores that adopt proper policies to utilize it as an instrument to reach consumers. The stores are able to accommodate group demand at a price lower than regular price in most circumstances but still manage to earn stable profits. The presence of regular consumers has a subtle effect on equilibrium formation, by strengthening the stores＇ power in negotiating with GB consumers to make group price weakly increase with group size. Moreover, competing stores are able to manipulate the interactions between purchase groups and collectively earn a higher total profit than a monopolist store when GB consumers account for a small fraction of market base and competition is intense.