The trade-off between obtaining a good distribution of Pareto-optimal solutions and obtaining them in a small computational time is an important issue in evolutionary multi-objective optimization (EMO). It has been well established in the EMO literature that although SPEA produces a better distribution compared to NSGA-II, the computational time needed to run SPEA is much larger. In this paper, we suggest a clustered NSGA-II which uses an identical clustering technique to that used in SPEA for obtaining a better distribution. Moreover, we propose a steady-state MOEA based on e-dominance concept and efficient parent and archive update strategies. Based on a comparative study on a number of two and three objective test problems, it is observed that the steady-state MOEA achieves a comparable distribution to the clustered NSGA-II with a much less computational time.

Towards a quick computation of well-spread pareto-optimal solutions

Due to the climate change and the rapid progress of urbanization, extreme weather disasters such as urban rainstorm and waterlogging are frequent. Therefore, how to find the waterlogging points in the presence of disasters and how to optimize the distribution of urban emergency logistics and reduce the negative impact of disasters have become a hot and difficult issue for government departments and scholars. First of all, the idea and method of using the big data of microblogging to obtain urban rainstorm and waterlogging disasters and public sentiment are put forward. In addition,this thesis constructed the location-routing problem model of urban emergency logistics in the situation of rainstorm and waterlogging disaster, and found out the dynamic emergency distribution path of Nanjing in the situation of waterlogging disaster by using NSGA-III algorithm. Research shows that the risk management of urban rainstorm and waterlogging disasters, together with social media data, is a feasible way to obtain on-site data of disasters and carry out risk assessment of disasters. At the same time, the emergency logistics location-positioning model and algorithm can provide a reference for similar disaster emergency logistics distribution network and the conclusion can provide empirical reference for cities to cope with rainstorm and waterlogging disasters.

Finding of urban rainstorm and waterlogging disasters based on microblogging data and the location-routing problem model of urban emergency logistics

For more than ten years, online job boards have provided their services to both job seekers and employers who want to hire potential candidates. The provided services are generally based on traditional information retrieval techniques, which may not be appropriate for both job seekers and employers. The reason is that the number of produced results for job seekers may be enormous. Therefore, they are required to spend time reading and reviewing their finding criteria. Reciprocally, recruitment is a crucial process for every organization. Identifying potential candidates and matching them with job offers requires a wide range of expertise and knowledge. This article proposes a reciprocal recommendation based on bi-directional correspondence as a way to support both recruiters’ and job seekers’ work. Recruiters can find the best-fit candidates for every job position in their job postings, and job seekers can find the best-match jobs to match their resumes. We show how machine learning can solve problems in natural language processing of text content and similarity scores depending on job offers in major Saudi cities scraped from Indeed. For bi-directional matching, a similarity calculation based on the integration of explicit and implicit job information from two sides (recruiters and job seekers) has been used. The proposed system is evaluated using a resume/job offer dataset. The performance of generated recommendations is evaluated using decision support measures. Obtained results confirm that the proposed system can not only solve the problem of bi-directional recommendation, but also improve the prediction accuracy.

/pdf/nlp-based-bi-directional-recommendation-system-towards-21tm4swn.pdf

NLP-Based Bi-Directional Recommendation System: Towards Recommending Jobs to Job Seekers and Resumes to Recruiters

This paper mainly investigates the free vibration behaviors of functionally graded porous (FGP) cylindrical panels and shells. According to the direction and type of porosity distribution, besides three typical thickness-direction distribution kinds: symmetric, non-symmetric and uniform, two new distribution types along the length direction: symmetric and non-symmetric are considered for the first time. By utilizing the first order shear deformation theory (FSDT) in conjunction with Hamilton’s principle, the weak form for free vibration of FGP shells is derived. Then the isogeometric analysis (IGA) method is applied to solve this problem, in which the non-uniform rational B-spline (NURBS) is employed to both exactly build geometric model and approximately describe displacement fields. The accuracy of IGA-FSDT is examined via comparing the current results with published data. Several numerical examples for FGP cylindrical panels and shells are presented and discussed in terms of porosity coefficient, boundary conditions, geometric parameters and types of porosity distributions. Some innovative results may provide benchmark solutions for other algorithm research and some guidelines for designing FGP structures. 

Free vibration analysis of functionally graded porous cylindrical panels and shells with porosity distributions along the thickness and length directions

Job recommender systems (JRS) are a subclass of information filtering systems that aims to help job seekers identify what might match their skills and experiences and prevent them from being lost in the vast amount of information available on job boards that aggregates postings from many sources such as LinkedIn or Indeed. A variety of strategies used as part of JRS have been implemented, most of them failed to recommend job vacancies that fit properly to the job seekers profiles when dealing with more than one job offer. They consider skills as passive entities associated with the job description, which need to be matched for finding the best job recommendation. This paper provides a recommender system to assist job seekers in finding suitable jobs based on their resumes. The proposed system recommends the top-n jobs to the job seekers by analyzing and measuring similarity between the job seeker’s skills and explicit features of job listing using content-based filtering. First-hand information was gathered by scraping jobs description from Indeed from major cities in Saudi Arabia (Dammam, Jeddah, and Riyadh). Then, the top skills required in job offers were analyzed and job recommendation was made by matching skills from resumes to posted jobs. To quantify recommendation success and error rates, we sought to compare the results of our system to reality using decision support measures. 

/pdf/learning-based-matched-representation-system-for-job-1s8wub2v.pdf

Learning-Based Matched Representation System for Job Recommendation

Variational quantum extreme learning machine

In this research, the natural frequency behavior of functionally graded (FG) porous joined hemispherical–cylindrical–hemispherical shell vessels reinforced by graphene platelet (GPLs) has been studied for the first time. Three various types of porosity distribution are assumed through the thickness direction of shell vessel. In the two types of porosity patterns, a pattern of porosities in metal matrix is symmetric and the other one is uniform. Besides, five GPL patterns are assumed for dispersing of GPLs in metal matrix. Extended role of mixture and Tsai-Halpin is used to determine the mass density and Young’s modulus of elasticity of the structure, respectively. By employing 3D elasticity theory, Hamilton’s Principal and FEM in conjunction with Rayleigh–Ritz method, the governing equations of motion of the joined shell vessel are obtained and natural frequencies are extracted. The impact of various factors such as coefficient of porosity, several porosity patterns along with different GPLs distributions and weight fraction of graphene nanofillers on natural frequency behavior of FG porous joined hemispherical–cylindrical–hemispherical shell vessels reinforced by GPLs nanofillers has been reported for the first time. 

Free vibration response of FG porous joined hemispherical- cylindrical- hemispherical shell vessels reinforced by graphene platelet

Cachexia is characterized by progressive weight loss accompanied by the loss of specific skeletal muscle and adipose tissue. Increased lactate production, either due to the Warburg effect from tumors or accelerated glycolysis effects from cachectic muscle, is the most dangerous factor for cancer cachexia. This study aimed to explore the efficiency of 2-deoxy-D-glucose (2-DG) in blocking Cori cycle activity and its therapeutic effect on cachexia-associated muscle wasting. A C26 adenocarcinoma xenograft model was used to study cancer cachectic metabolic derangements. Tumor-free lean mass, hindlimb muscle morphology, and fiber-type composition were measured after in vivo 2-DG administration. Activation of the ubiquitin-dependent proteasome pathway (UPS) and autophagic–lysosomal pathway (ALP) was further assessed. The cachectic skeletal muscles of tumor-bearing mice exhibited altered glucose and lipid metabolism, decreased carbohydrate utilization, and increased lipid β-oxidation. Significantly increased gluconeogenesis and decreased ketogenesis were observed in cachectic mouse livers. 2-DG significantly ameliorated cancer cachexia-associated muscle wasting and decreased cachectic-associated lean mass levels and fiber cross-sectional areas. 2-DG inhibited protein degradation-associated UPS and ALP, increased ketogenesis in the liver, and promoted ketone metabolism in skeletal muscle, thus enhancing mitochondrial bioenergetic capacity. 2-DG effectively prevents muscle wasting by increasing ATP synthesis efficiency via the ketone metabolic pathway and blocking the abnormal Cori cycle.

/pdf/2-deoxy-d-glucose-alleviates-cancer-cachexia-induced-muscle-1eywm62u.pdf

2-Deoxy-D-glucose Alleviates Cancer Cachexia-Induced Muscle Wasting by Enhancing Ketone Metabolism and Inhibiting the Cori Cycle

During recent years, for its simplicity and efficiency, the non-dominated-sorting algorithm (NSGA-II) has been widely applied to solve multi-objective optimization problems. However, in the canonical NSGA-II, the resulted population may have multiple individuals with the same fitness values, and which makes the resulted population lack of diversity. To solve this kind of problem, in this study, we propose a developed NSGA-II algorithm (hereafter called NSGA-II-D). In NSGA-II-D, a novel duplicate individuals cleaning procedure is embedded to delete the individuals the same fitness values with other ones. Then, the proposed algorithm is tested on the well-known ZDT1 instance to verify the efficiency and performance. Finally, to solve the realisitc optimization problem in intelligent building system, we select a well-known optimal chiller loading (OCL) problem to test the ability to maintain population diversity. Experimental results on the benchmarks show the efficiency and effectiveness of the proposed algorithm.

A Developed NSGA-II Algorithm for Multi-objective Chiller Loading Optimization Problems

A modified multi-objective evolutionary algorithm based on decomposition (MOEA/D) is used to solve the optimal chiller loading (OCL) problem. In a multi-chiller system, the chillers are usually partially loaded for most of the running time. If the chillers are unreasonably managed, their consumption noticeably increases. To reduce power consumption, the partial load ratio (PLR) of each chiller must be adjusted. The system must meet the system cooling load (CL), so, it is a constrained optimization problem. This study uses a multi-objective method to solve the constrained optimization. The constraint condition is changed to a new objective, so, the problem can be solved as a multi-objective problem. Comparison with the experimental results in the literature proved the effectiveness and performance of the modified algorithm, which can be fully applied in air conditioning system operations.

Optimal Chiller Loading by MOEA/D for Reducing Energy Consumption

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