Behavioral Mapping and Post-Occupancy Evaluation of Meeting-Point Design in an International Airport

The meeting behavior is a pervasive kind of interaction, which often occurs between the passenger and the shuttle. However, the meeting point set up at the Taoyuan International Airport is too far from the entry-exit, often causing passengers to stop searching near the entry-exit. When the number of people waiting for the rush hour increases, it often results in chaos in the waiting area. This study tried to find out what is the key factor to promote the rapid finding of each other between the passengers and the pick-ups. Then we implemented several design proposals to improve the meeting behavior of passengers and pick-ups based on behavior mapping and post-occupancy evaluation to enhance their meeting efficiency in unfamiliar environments. The research base is the reception hall of the second terminal of Taoyuan International Airport. Behavioral observation and mapping are implemented on the entry of inbound passengers into the welcome space, including the crowd distribution of the people who rely on the separation wall in the waiting area, the behavior of meeting and the interaction between the inbound passengers and the pick-ups. Then we redesign the space planning and signage design based on post-occupancy evaluation to verify the effectiveness of space plan and signage design. This study found that passengers ignore existing meeting-point designs which are placed on distant pillars at both ends. The position of the screen affects the area where the receiver is stranded, causing the pick-ups to block the passenger's moving line. The pick-ups prefer to wait where it is easy to watch incoming passengers and where it is closest to the mode of transport they take when leaving. Large visitors tend to gather next to landmarks, and smaller groups have a wide waiting area in the lobby. The location of the meeting point chosen by the pick-ups is related to the view of the incoming passenger. Finally, this study proposes an improved design of the meeting point, setting the traffic information in it, so that most passengers can see the traffic information when they enter the country. At the same time, we also redesigned the pick-ups desk to improve the efficiency of passenger meeting.

Single Valued Neutrosophic Hesitant Fuzzy Rough Set and Its Application

In this paper, we proposed the notion of single valued neutrosophic hesitant fuzzy rough set, by combining single valued neutrosophic hesitant fuzzy set and rough set. The combination of single valued neutrosophic hesitant fuzzy set and rough set is a powerful tool for dealing with uncertainty, granularity and incompleteness of knowledge in information systems. We presented both definition and some basic properties of the proposed model. Finally, we gave a general approach which is applied to a decision making problem in disease diagnoses, and demonstrated the effectiveness of the approach by a numerical example.

Entrepreneurship Skills Acquisition through Education: Impact of the Nurturance of Knowledge, Skills, and Attitude on New Venture Creation

Entrepreneurship through higher education has taken a paradigm shift from traditional classroom lecture series method to a modern approach, which lay emphasis on nurturing competencies, enhancing knowledge, skills, attitudes/abilities (KSA), which has positive impact on the development of core capabilities. The present paper was focused on the analysis of entrepreneurship education as a pedagogical intervention for the post-graduate program offered at the Entrepreneurship Development Institute of India, Gujarat, India. The study is focused on a model with special emphasis on developing KSA and its effect on nurturing entrepreneurial spirit within students. The findings represent demographic and thematic assessment of the implemented pedagogical model with an outcome of students choosing a career in new venture creation or growth/diversification of family owned businesses. This research will be helpful for academicians, research scholars, potential entrepreneurs, ecosystem enablers and students to infer the effectiveness of nurturing entrepreneurial skills and bringing more changes in personal attitudes by the way of enhancing the knowledge and skills required for the execution of an entrepreneurial career. This research is original in nature as it provides an in-depth insight into an implemented model of curriculum, focused on the development and nurturance of basic skills and its impact on the career choice of students.

Effectiveness Evaluation of a Machine Design Process Based on the Computation of the Specific Output

In this paper, effectiveness of a machine design process is evaluated on the basis of the specific output calculus. Concretely, a screw-worm gear mechanical transmission is designed by using the classical and the 3D-CAD methods. Strength analysis and drawing of the designed parts is substantially aided by employing the SolidWorks software. Quality of the design process is assessed by manufacturing (printing) the parts, and by computing the efficiency, specific load, as well as the specific output (work) of the mechanical transmission. Influence of the stroke, travelling velocity and load on the mechanical output, is emphasized. Optimal design of the mechanical transmission becomes possible by the appropriate usage of the acquired results.

Path-Tracking Controller for Tracked Mobile Robot on Rough Terrain

Automation technologies for agriculture field are needed to promote labor-saving. One of the most relevant problems in automated agriculture is represented by controlling the robot along a predetermined path in presence of rough terrain or incline ground. Unfortunately, disturbances originating from interaction with the ground, such as slipping, make it quite difficult to achieve the required accuracy. In general, it is required to move within 5-10 cm accuracy with respect to the predetermined path. Moreover, lateral velocity caused by gravity on the incline field also affects slipping. In this paper, a path-tracking controller for tracked mobile robots moving on rough terrains of incline field such as vineyard is presented. The controller is composed of a disturbance observer and an adaptive controller based on the kinematic model of the robot. The disturbance observer measures the difference between the measured and the reference yaw rate and linear velocity in order to estimate slip. Then, the adaptive controller adapts “virtual” parameter of the kinematics model: Instantaneous Centers of Rotation (ICRs). Finally, target angular velocity reference is computed according to the adapted parameter. This solution allows estimating the effects of slip without making the model too complex. Finally, the effectiveness of the proposed solution is tested in a simulation environment.

Standalone Docking Station with Combined Charging Methods for Agricultural Mobile Robots

One of the biggest concerns in the field of agriculture is around the energy efficiency of robots that will perform agriculture’s activity and their charging methods. In this paper, two different charging methods for agricultural standalone docking stations are shown that will take into account various variants as field size and its irregularities, work’s nature to which the robot will perform, deadlines that have to be respected, among others. Its features also are dependent on the orchard, season, battery type and its technical specifications and cost. First charging base method focuses on wireless charging, presenting more benefits for small field. The second charging base method relies on battery replacement being more suitable for large fields, thus avoiding the robot stop for recharge. Existing many methods to charge a battery, the CC CV was considered the most appropriate for either simplicity or effectiveness. The choice of the battery for agricultural purposes is if most importance. While the most common battery used is Li-ion battery, this study also discusses the use of graphene-based new type of batteries with 45% over capacity to the Li-ion one. A Battery Management Systems (BMS) is applied for battery balancing. All these approaches combined showed to be a promising method to improve a lot of technical agricultural work, not just in terms of plantation and harvesting but also about every technique to prevent harmful events like plagues and weeds or even to reduce crop time and cost.

Estimating the Traffic Impacts of Green Light Optimal Speed Advisory Systems Using Microsimulation

Even though signalised intersections are necessary for urban road traffic management, they can act as bottlenecks and disrupt traffic operations. Interrupted traffic flow causes congestion, delays, stop-and-go conditions (i.e. excessive acceleration/deceleration) and longer journey times. Vehicle and infrastructure connectivity offers the potential to provide improved new services with additional functions of assisting drivers. This paper focuses on one of the applications of vehicle-to-infrastructure communication namely Green Light Optimal Speed Advisory (GLOSA). To assess the effectiveness of GLOSA in the urban road network, an integrated microscopic traffic simulation framework is built into VISSIM software. Vehicle movements and vehicle-infrastructure communications are simulated through the interface of External Driver Model. A control algorithm is developed for recommending an optimal speed that is continuously updated in every time step for all vehicles approaching a signal-controlled point. This algorithm allows vehicles to pass a traffic signal without stopping or to minimise stopping times at a red phase. This study is performed with all connected vehicles at 100% penetration rate. Conventional vehicles are also simulated in the same network as a reference. A straight road segment composed of two opposite directions with two traffic lights per lane is studied. The simulation is implemented under 150 vehicles per hour and 200 per hour traffic volume conditions to identify how different traffic densities influence the benefits of GLOSA. The results indicate that traffic flow is improved by the application of GLOSA. According to this study, vehicles passed through the traffic lights more smoothly, and waiting times were reduced by up to 28 seconds. Average delays decreased for the entire network by 86.46% and 83.84% under traffic densities of 150 vehicles per hour per lane and 200 vehicles per hour per lane, respectively.

Simulation Data Summarization Based on Spatial Histograms

In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

An Integrated Solid Waste Management Strategy for Semi-Urban and Rural Areas of Pakistan

In Pakistan, environmental degradation and consequent human health deterioration has rapidly accelerated in the past decade due to solid waste mismanagement. As the situation worsens with time, establishment of proper waste management practices is urgently needed especially in semi urban and rural areas of Pakistan. This study uses a concept of Waste Bank, which involves a transfer station for collection of sorted waste fractions and its delivery to the targeted market such as recycling industries, biogas plants, composting facilities etc. The management efficiency and effectiveness of Waste Bank depend strongly on the proficient sorting and collection of solid waste fractions at household level. However, the social attitude towards such a solution in semi urban/rural areas of Pakistan demands certain prerequisites to make it workable. Considering these factors the objectives of this study are to: [A] Obtain reliable data about quantity and characteristics of generated waste to define feasibility of business and design factors, such as required storage area, retention time, transportation frequency of the system etc. [B] Analyze the effects of various social factors on waste generation to foresee future projections. [C] Quantify the improvement in waste sorting efficiency after awareness campaign. We selected Gujrat city of Central Punjab province of Pakistan as it is semi urban adjoined by rural areas. A total of 60 houses (20 from each of the three selected colonies), belonging to different social status were selected. Awareness sessions about waste segregation were given through brochures and individual lectures in each selected household. Sampling of waste, that households had attempted to sort, was then carried out in the three colored bags that were provided as part of the awareness campaign. Finally, refined waste sorting, weighing of various fractions and measurement of dry mass was performed in environmental laboratory using standard methods. It was calculated that sorting efficiency of waste improved from 0 to 52% as a result of the awareness campaign. The generation of waste (dry mass basis) on average from one household was 460 kg/year whereas per capita generation was 68 kg/year. Extrapolating these values for Gujrat Tehsil, the total waste generation per year is calculated to be 101921 tons dry mass (DM). Characteristics found in waste were (i) organic decomposable (29.2%, 29710 tons/year DM), (ii) recyclables (37.0%, 37726 tons/year DM) that included plastic, paper, metal and glass, and (iii) trash (33.8%, 34485 tons/year DM) that mainly comprised of polythene bags, medicine packaging, pampers and wrappers. Waste generation was more in colonies with comparatively higher income and better living standards. In future, data collection for all four seasons and improvements due to expansion of awareness campaign to educational institutes will be quantified. This waste management system can potentially fulfill vital sustainable development goals (e.g. clean water and sanitation), reduce the need to harvest fresh resources from the ecosystem, create business and job opportunities and consequently solve one of the most pressing environmental issues of the country.

A Fuzzy TOPSIS Based Model for Safety Risk Assessment of Operational Flight Data

Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.

Dynamic Measurement System Modeling with Machine Learning Algorithms

In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Implementation of Edge Detection Based on Autofluorescence Endoscopic Image of Field Programmable Gate Array

Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

State Estimation Based on Unscented Kalman Filter for Burgers’ Equation

Controlling the flow of fluids is a challenging problem that arises in many fields. Burgers’ equation is a fundamental equation for several flow phenomena such as traffic, shock waves, and turbulence. The optimal feedback control method, so-called model predictive control, has been proposed for Burgers’ equation. However, the model predictive control method is inapplicable to systems whose all state variables are not exactly known. In practical point of view, it is unusual that all the state variables of systems are exactly known, because the state variables of systems are measured through output sensors and limited parts of them can be only available. In fact, it is usual that flow velocities of fluid systems cannot be measured for all spatial domains. Hence, any practical feedback controller for fluid systems must incorporate some type of state estimator. To apply the model predictive control to the fluid systems described by Burgers’ equation, it is needed to establish a state estimation method for Burgers’ equation with limited measurable state variables. To this purpose, we apply unscented Kalman filter for estimating the state variables of fluid systems described by Burgers’ equation. The objective of this study is to establish a state estimation method based on unscented Kalman filter for Burgers’ equation. The effectiveness of the proposed method is verified by numerical simulations.

An Enhanced Particle Swarm Optimization Algorithm for Multiobjective Problems

Multiobjective Particle Swarm Optimization (MOPSO) has shown an effective performance for solving test functions and real-world optimization problems. However, this method has a premature convergence problem, which may lead to lack of diversity. In order to improve its performance, this paper presents a hybrid approach which embedded the MOPSO into the island model and integrated a local search technique, Variable Neighborhood Search, to enhance the diversity into the swarm. Experiments on two series of test functions have shown the effectiveness of the proposed approach. A comparison with other evolutionary algorithms shows that the proposed approach presented a good performance in solving multiobjective optimization problems.

Investigation of Some Flotation Parameters and the Role of Dispersants in the Flotation of Chalcopyrite

A suitable choice of flotation parameters and reagents have a strong effect on the effectiveness of flotation process. The objective of this paper is to give an overview of the flotation of chalcopyrite with the different conditions and dispersants. Flotation parameters such as grinding time, pH, type, and dosage of dispersant were investigated. In order to understand the interaction of some dispersants, sodium silicate, sodium hexametaphosphate and sodium polyphosphate were used. The optimum results were obtained at a pH of 11.5 and a grinding time of 10 minutes. A copper concentrate was produced assaying 29.85% CuFeS2 and 65.97% flotation recovery under optimum rougher flotation conditions with sodium silicate.

Multilevel Arnoldi-Tikhonov Regularization Methods for Large-Scale Linear Ill-Posed Systems

This paper is devoted to the numerical solution of large-scale linear ill-posed systems. A multilevel regularization method is proposed. This method is based on a synthesis of the Arnoldi-Tikhonov regularization technique and the multilevel technique. We show that if the Arnoldi-Tikhonov method is a regularization method, then the multilevel method is also a regularization one. Numerical experiments presented in this paper illustrate the effectiveness of the proposed method.

A Genetic Algorithm Approach Considering Zero Injection Bus Constraint Modeling for Optimal Phasor Measurement Unit Placement

This paper presents optimal Phasor Measurement Unit (PMU) Placement in network using a genetic algorithm approach as it is infeasible and require high installation cost to place PMUs at every bus in network. This paper proposes optimal PMU allocation considering observability and redundancy utilizing Genetic Algorithm (GA) approach. The nonlinear constraints of buses are modeled to give accurate results. Constraints associated with Zero Injection (ZI) buses and radial buses are modeled to optimize number of locations for PMU placement. GA is modeled with ZI bus constraints to minimize number of locations without losing complete observability. Redundancy of every bus in network is computed to show optimum redundancy of complete system network. The performance of method is measured by Bus Observability Index (BOI) and Complete System Observability Performance Index (CSOPI). MATLAB simulations are carried out on IEEE -14, -30 and -57 bus-systems and compared with other methods in literature survey to show the effectiveness of the proposed approach.

State Estimation Solution with Optimal Allocation of Phasor Measurement Units Considering Zero Injection Bus Modeling

This paper presents state estimation with Phasor Measurement Unit (PMU) allocation to obtain complete observability of network. A matrix is designed with modeling of zero injection constraints to minimize PMU allocations. State estimation algorithm is developed with optimal allocation of PMUs to find accurate states of network. The incorporation of PMU into traditional state estimation process improves accuracy and computational performance for large power systems. The nonlinearity integrated with zero injection (ZI) constraints is remodeled to linear frame to optimize number of PMUs. The problem of optimal PMU allocation is regarded with modeling of ZI constraints, PMU loss or line outage, cost factor and redundant measurements. The proposed state estimation with optimal PMU allocation has been compared with traditional state estimation process to show its importance. MATLAB programming on IEEE 14, 30, 57, and 118 bus networks is implemented out by Binary Integer Programming (BIP) method and compared with other methods to show its effectiveness.

The Effectiveness of National Fiscal Rules in the Asia-Pacific Countries

This study utilizes the International Monetary Fund (IMF) Fiscal Rules Dataset focusing on four specific fiscal rules such as expenditure rule, revenue rule, budget balance rule, and debt rule and five main characteristics of each fiscal rule those are monitoring, enforcement, coverage, legal basis, and escape clause to construct the Fiscal Rule Index for nine countries in the Asia-Pacific region from 1996 to 2015. After constructing the fiscal rule index for each country, we utilize the Panel Generalized Method of Moments (Panel GMM) by using the constructed fiscal rule index to examine the effectiveness of fiscal rules in reducing procyclicality. Empirical results show that national fiscal rules have a significantly negative impact on procyclicality of government expenditure. Additionally, stricter fiscal rules combined with high government effectiveness are effective in reducing procyclicality of government expenditure. Results of this study indicate that for nine Asia-Pacific countries, policymakers’ use of fiscal rules and government effectiveness to reducing procyclicality of fiscal policy are effective.

A Wireless Feedback Control System as a Base of Bio-Inspired Structure System to Mitigate Vibration in Structures

This paper attempts to develop a wireless feedback control system as a primary step eventually toward a bio-inspired structure system where inanimate structure behaves like a life form autonomously. It is a standalone wireless control system which is supposed to measure externally caused structural responses, analyze structural state from acquired data, and take its own action on the basis of the analysis with an embedded logic. For an experimental examination of its effectiveness, we applied it on a model of two-span bridge and performed a wireless control test. Experimental tests have been conducted for comparison on both the wireless and the wired system under the conditions of Un-control, Passive-off, Passive-on, and Lyapunov control algorithm. By proving the congruence of the test result of the wireless feedback control system with the wired control system, its control performance was proven to be effective. Besides, it was found to be economical in energy consumption and also autonomous by means of a command algorithm embedded into it, which proves its basic capacity as a bio-inspired system.