A Building Information Modeling-Life Cycle Cost Analysis Integrated Model to Enhance Decisions Related to the Selection of Construction Methods at the Conceptual Design Stage of Buildings

Life Cycle Cost Analysis (LCCA) provides a systematic approach to assess the total cost associated with owning, operating, and maintaining assets throughout their entire life. BIM empowers architects and designers to perform real-time evaluations to explore various design options. However, when integrated with LCCA, BIM provides a comprehensive economic perspective that helps stakeholders understand the long-term financial implications of design decisions. This study presents a methodology for developing a model that seamlessly integrates BIM and LCCA during the conceptual design stage of buildings. This integration allows for a comprehensive evaluation and analysis of the design process, ensuring that the development aligns with the principles of low carbon emissions by employing modular construction, 3D concrete printing methods, and different building design alternatives. The model considers the initial construction costs in addition to all the long-term operational, maintenance, and salvage values. It combines various tools and data through different modules, including energy analysis, Life Cycle Assessment (LCA), and Life Cycle Cost Analysis (LCCA) to execute a comprehensive assessment of the financial implications of a specific design option throughout the lifecycle of building projects. The development of the said model and its implementation involves the creation of a new plug-in for the BIM tool (i.e., Autodesk Revit) to enhance its functionalities and capabilities in forecasting the life-cycle costs of buildings in addition to generating associated cash flows, creating scenarios, and sensitivity analyses in an automatic manner. This model empowers designers to evaluate and justify their initial investments while designing and selecting potential construction methods for buildings, and enabling stakeholders to make informed decisions by assessing different design alternatives based on long-term financial considerations during the early stages of design.

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

An Analysis Model of Learners’ Online Learning Status Based on Deep Neural Network and Multi-Dimensional Information Fusion

The learning status of learners directly affects the quality of learning.Compared with offline teachers,it is difficult for online teachers to capture the learning status of students in the whole class,and it is even more difficult to continue to pay attention to studentswhile teaching.Therefore,this paper proposes an online learning state analysis model based on a convolutional neural network and multi-dimensional information fusion.Specifically,a facial expression recognition model and an eye state recognition model are constructed to detect students’emotions and fatigue,respectively.By integrating the detected data with the homework test score data after online learning,an analysis model of students’online learning status is constructed.According to the PAD model,the learning state is expressed as three dimensions of students’understanding,engagement and interest,and then analyzed from multiple perspectives.Finally,the proposed model is applied to actual teaching,and procedural analysis of 5 different types of online classroom learners is carried out,and the validity of the model is verified by comparing with the results of the manual analysis.

Geographical origin identification of winter jujube(Ziziphus jujuba Dongzao')by using multi-element fingerprinting with chemometrics

Winter jujube(Ziziphus jujuba'Dongzao')is greatly appreciated by consumers for its excellent quality,but brand infringement frequently occurs in the market.Here,we first determined a total of 38 elements in 167 winter jujube samples from the main winter jujube producing areas of China by inductively coupled plasma mass spectrometer(ICP-MS).As a result,16 elements(Mg,K,Mn,Cu,Zn,Mo,Ba,Be,As,Se,Cd,Sb,Ce,Er,Tl,and Pb)exhibited significant differences in samples from different producing areas.Supervised linear discriminant analysis(LDA)and orthogonal projection to latent structures discriminant analysis(OPLS-DA)showed better performance in identifying the origin of samples than unsupervised principal component analysis(PCA).LDA and OPLS-DA had a mean identification accuracy of 87.84 and 94.64%in the testing set,respectively.By using the multilayer perceptron(MLP)and C5.0,the prediction accuracy of the models could reach 96.36 and 91.06%,respectively.Based on the above four chemometric methods,Cd,Tl,Mo and Se were selected as the main variables and principal markers for the origin identification of winter jujube.Overall,this study demonstrates that it is practical and precise to identify the origin of winter jujube through multi-element fingerprint analysis with chemometrics,and may also provide reference for establishing the origin traceability system of other fruits.

Side-Channel Leakage Analysis of Inner Product Masking

The Inner Product Masking(IPM)scheme has been shown to provide higher theoretical security guarantees than the BooleanMasking(BM).This scheme aims to increase the algebraic complexity of the coding to achieve a higher level of security.Some previous work unfolds when certain(adversarial and implementation)conditions are met,and we seek to complement these investigations by understanding what happens when these conditions deviate from their expected behaviour.In this paper,we investigate the security characteristics of IPM under different conditions.In adversarial condition,the security properties of first-order IPMs obtained through parametric characterization are preserved in the face of univariate and bivariate attacks.In implementation condition,we construct two new polynomial leakage functions to observe the nonlinear leakage of the IPM and connect the security order amplification to the nonlinear function.We observe that the security of IPMis affected by the degree and the linear component in the leakage function.In addition,the comparison experiments from the coefficients,signal-to-noise ratio(SNR)and the public parameter show that the security properties of the IPM are highly implementation-dependent.

Orbit Weighting Scheme in the Context of Vector Space Information Retrieval

This study introduces the Orbit Weighting Scheme(OWS),a novel approach aimed at enhancing the precision and efficiency of Vector Space information retrieval(IR)models,which have traditionally relied on weighting schemes like tf-idf and BM25.These conventional methods often struggle with accurately capturing document relevance,leading to inefficiencies in both retrieval performance and index size management.OWS proposes a dynamic weighting mechanism that evaluates the significance of terms based on their orbital position within the vector space,emphasizing term relationships and distribution patterns overlooked by existing models.Our research focuses on evaluating OWS’s impact on model accuracy using Information Retrieval metrics like Recall,Precision,InterpolatedAverage Precision(IAP),andMeanAverage Precision(MAP).Additionally,we assessOWS’s effectiveness in reducing the inverted index size,crucial for model efficiency.We compare OWS-based retrieval models against others using different schemes,including tf-idf variations and BM25Delta.Results reveal OWS’s superiority,achieving a 54%Recall and 81%MAP,and a notable 38%reduction in the inverted index size.This highlights OWS’s potential in optimizing retrieval processes and underscores the need for further research in this underrepresented area to fully leverage OWS’s capabilities in information retrieval methodologies.

Qualitative analysis of aromatic compounds via 1D TOCSY techniques

The aromatic compounds,including o-xylene,m-xylene,p-xylene,and ethylbenzene,primarily originate from the catalytic reforming of crude oil,and have a wide variety of applications.However,because of similar physical and chemical properties,these compounds are difficult to be identified by gas chromatography(GC)without standard samples.With the development of modern nuclear magnetic resonance(NMR)techniques,NMR has emerged as a powerful and efficient tool for the rapid analysis of complex and crude mixtures without purification.In this study,the parameters of one-dimensional(1D)total correlation spectroscopy(TOCSY)NMR techniques,including 1D selective gradient TOCSY and 1D chemicalshift-selective filtration(CSSF)with TOCSY,were optimized to obtain comprehensive molecular structure information.The results indicate that the overlapped signals in NMR spectra of nonpolar aromatic compounds(including o-xylene,m-xylene,p-xylene and ethylbenzene),polar aromatic compounds(benzyl alcohol,benzaldehyde,benzoic acid),and aromatic compounds with additional conjugated bonds(styrene)can be resolved in 1D TOCSY.More importantly,full molecular structures can be clearly distinguished by setting appropriate mixing time in 1D TOCSY.This approach simplifies the NMR spectra,provides structural information of entire molecules,and can be applied for the analysis of other structural isomers.

A Paraffin Sectioning Method Without Using the Microtome and an Analysis Method for Optical Information of the Plant Anatomical Digital Photographs

[Objective] The research aimed to study a paraffin method without using the microtome,and also introduced an analysis method for optical information of the plant anatomical digital photographs.[Method] The plant material softened or not was embedded in paraffin according to the paraffin method.Cut the thin paraffin sections from the paraffin block with a sharp two-sided blade under anatomical lens.The thin material sections rolled up when they were cut off.Took the section rolls to a slide,and then heated them to melt the paraffin section roll.When the paraffin melted,the sections of plant material were rolled out.After the common or simplified procedures of staining and mounting,the preparations were finished.When an anatomical digital photograph was processed,copy it into the word file and two copies of the original photograph were obtained.One copy was selected to make it to be a negative photograph,and then press the key ＂Press Screen＂ to copy the screen frame.After it was copied into the word file,cut of the unnecessary parts and other operations were carried out,then processed photograph was obtained.[Results] The anatomical preparation for research was gotten.The analyzed digital photograph of the leaf structure of Salix matsudana var.matsudana f.tortuosa has some a three-dimensional effect,and the different leaf structures and cells,e.g.cuticle,cell wall,protoplast,vein,etc.can be identified easily.[Conclusion]The paraffin method without using the microtome has advantages of low cost and higher efficiency,which could be applied by the beginner or in the time without a microtome to be used.The analysis of the plant anatomical digital photographs can acquire more structural information than the original digital photographs,which shows the potentiality and prospects of the optical information analysis of the microscopic imagery and its digital photograph.

Integrating Virtual Reality and Energy Analysis with BIM to Optimize Window-to-Wall Ratio and Building’s Orientation for Age-in-Place Design at the Conceptual Stage

This study unfolds an innovative approach aiming to address the critical role of building design in global energy consumption, focusing on optimizing the Window-to-Wall Ratio (WWR), since buildings account for approximately 30% of total energy consumed worldwide. The greatest contributors to energy expenditure in buildings are internal artificial lighting and heating and cooling systems. The WWR, determined by the proportion of the building’s glazed area to its wall area, is a significant factor influencing energy efficiency and minimizing energy load. This study introduces the development of a semi-automated computer model designed to offer a real-time, interactive simulation environment, fostering improving communication and engagement between designers and owners. The said model serves to optimize both the WWR and building orientation to align with occupants’ needs and expectations, subsequently reducing annual energy consumption and enhancing the overall building energy performance. The integrated model incorporates Building Information Modeling (BIM), Virtual Reality (VR), and Energy Analysis tools deployed at the conceptual design stage, allowing for the amalgamation of owners’ inputs in the design process and facilitating the creation of more realistic and effective design strategies.

Application of evidence theory in information fusion of multiple sources in bayesian analysis

How to obtain proper prior distribution is one of the most critical problems in Bayesian analysis. In many practical cases, the prior information often comes from different sources, and the prior distribution form could be easily known in some certain way while the parameters are hard to determine. In this paper, based on the evidence theory, a new method is presented to fuse the information of multiple sources and determine the parameters of the prior distribution when the form is known. By taking the prior distributions which result from the information of multiple sources and converting them into corresponding mass functions which can be combined by Dempster-Shafer (D-S) method, we get the combined mass function and the representative points of the prior distribution. These points are used to fit with the given distribution form to determine the parameters of the prior distribution. And then the fused prior distribution is obtained and Bayesian analysis can be performed. How to convert the prior distributions into mass functions properly and get the representative points of the fused prior distribution is the central question we address in this paper. The simulation example shows that the proposed method is effective.

A new method to create depth information based on lighting analysis for 2D/3D conversion

A new method creating depth information for 2D/3D conversion was proposed. The distance between objects is determined by the distances between objects and light source position which is estimated by the analysis of the image. The estimated lighting value is used to normalize the image. A threshold value is determined by some weighted operation between the original image and the normalized image. By applying the threshold value to the original image, background area is removed. Depth information of interested area is calculated from the lighting changes. The final 3D images converted with the proposed method are used to verify its effectiveness.

A DDoS Attack Information Fusion Method Based on CNN for Multi-Element Data

Traditional distributed denial of service(DDoS)detection methods need a lot of computing resource,and many of them which are based on single element have high missing rate and false alarm rate.In order to solve the problems,this paper proposes a DDoS attack information fusion method based on CNN for multi-element data.Firstly,according to the distribution,concentration and high traffic abruptness of DDoS attacks,this paper defines six features which are respectively obtained from the elements of source IP address,destination IP address,source port,destination port,packet size and the number of IP packets.Then,we propose feature weight calculation algorithm based on principal component analysis to measure the importance of different features in different network environment.The algorithm of weighted multi-element feature fusion proposed in this paper is used to fuse different features,and obtain multi-element fusion feature(MEFF)value.Finally,the DDoS attack information fusion classification model is established by using convolutional neural network and support vector machine respectively based on the MEFF time series.Experimental results show that the information fusion method proposed can effectively fuse multi-element data,reduce the missing rate and total error rate,memory resource consumption,running time,and improve the detection rate.

Separate Analysis of Remote Sensing Information of Structures of Different Geological Periods and Quantitative Study of Corresponding Tectonic Stress Fields

The structural feature shown on a remote sensing image is a synthetic result ofcombination of the deformations produced during the entire geological history of an area.Therefore, the respective tectonic stress field of each of the different stages in the complexdeformation of an area can be reconstructed in three steps: (1) geological structures formed atdifferent times are distinguished in remote sensing image interpretation; (2) structuraldeformation fields at different stages are determined by analyzing relationships betweenmicrostructures (joints and fractures) and the related structures (folds and faults); and (3)tectonic stress fields at different stages are respectively recovered through a study of the featuresof structural deformation fields in different periods. Circular structures and related circlular and radial joints are correlated in space to con-cealed structural rises. The authors propose a new method for establishing a natural model ofthe concealed structural rises and calculating the tectonic stress field by using quantitative dataof the remote sensing information of circular structures and related linear structures.

Forecasting promising technology using analysis of patent information:Focused on next generation mobile communications

In order to forecast promising technologies in the field of next generation mobile communication, various patent indicators were analyzed such as citation per patent, patent family information, patent share, increase rate, and patent activity. These indicators were quantified into several indexes and then integrated into an evaluation score to provide promising technologies. As a result of the suggested patent analysis, four technologies out of twenty two in details classification were selected, which showed outstanding technology competitiveness, high patent share and increasing rates as well as high recent-patent-ratios and triad-patent-family-ratios. Each of the selected technologies scored more than 10 points in total, and the following four technologies were suggested as promising ones in the field of next generation mobile communication: 1) 3GPP based mobile communication, 2) beyond 4G mobile communication, 3) IEEE 802.16 based mobile communication, which are in medium classification of broadband mobile communication system, and 4) testing/certification system of mobile communication, which is in medium classification of mobile communication testing/certification system.

Is There an Information Field in the Life World？ Empirical Approach Using Electrophotonic Analysis

This paper presents a brief review of distant biological communication phenomena, information fields explained as a transduction of information without energy displacement, experimental requirements for testing this hypothesis with human beings using electrophotonic analysis, oxymetry and electromagnetic shielding. Finally, authors present preliminary results and future work on this new field of interdisciplinary research.

A comparative study of information diffusion in weblogs and microblogs based on social network analysis

Purpose: This paper intends to explore a quantitative method for investigating the characteristics of information diffusion through social media like weblogs and microblogs.By using the social network analysis methods,we attempt to analyze the different characteristics of information diffusion in weblogs and microblogs as well as the possible reasons of these differences.Design/methodology/approach: Using the social network analysis methods,this paper carries out an empirical study by taking the Chinese weblogs and microblogs in the field of Library and Information Science(LIS) as the research sample and employing measures such as network density,core/peripheral structure and centrality.Findings: Firstly,both bloggers and microbloggers maintain weak ties,and both of their social networks display a small-world effect. Secondly,compared with weblog users,microblog users are more interconnected,more equal and more capable of developing relationships with people outside their own social networks. Thirdly,the microblogging social network is more conducive to information diffusion than the blogging network,because of their differences in functions and the information flow mechanism. Finally,the communication mode emerged with microblogging,with the characteristics of micro-content,multi-channel information dissemination,dense and decentralized social network and content aggregation,will be one of the trends in the development of the information exchange platform in the future.Research limitations: The sample size needs to be increased so that samples are more representative. Errors may exist during the data collection. Moreover,the individual-level characteristics of the samples as well as the types of information exchanged need to be further studied.Practical implications: This preliminary study explores the characteristics of information diffusion in the network environment and verifies the feasibility of conducting a quantitative analysis of information diffusion through social media. In addition,it provides insight into the characteristics of information diffusion in weblogs and microblogs and the possible reasons of these differences.Originality/value: We have analyzed the characteristics of information diffusion in weblogs and microblogs by using the social network analysis methods. This research will be useful for a quantitative analysis of the underlying mechanisms of information flow through social media in the network environment.

The hot issues of studies in China on digital information resources: Based on co-word analysis

With the SPSS and the help of factor method and hierarchical clustered method,journal articles on digital information resources(DIR) from CNKI in the past ten years are analyzed with a co-word analytical method in this paper. The hot issues of studies on DIR and the relationship between those subjects are analyzed in this investigation as well.

Exploratory Data Analysis Applied in Mapping Multi-element Soil Geochemical Anomalies for Drill Target Definition:A Case Study from the Unpha Layered Non-magmatic Hydrothermal Pb-Zn Deposit,DPR Korea

A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization.A favorable main factor with a strong association of the elements Zn,Cu and Pb,related to mineralization,was selected for interpretation.The median+2 MAD(median absolute deviation)method of exploratory data analysis(EDA)and C-A(concentration-area)fractal modeling were then applied to the Mahalanobis distance,as defined by Zn,Cu and Pb from the factor analysis to set the thresholds for defining multi-element anomalies.As a result,the median+2 MAD method more successfully identified the Pb-Zn mineralization than the C-A fractal model.The soil anomaly identified by the median+2 MAD method on the Mahalanobis distances defined by three principal elements(Zn,Cu and Pb)rather than thirteen elements(Co,Zn,Cu,V,Mo,Ni,Cr,Mn,Pb,Ba,Sr,Zr and Ti)was the more favorable reflection of the ore body.The identified soil geochemical anomalies were compared with the in situ economic Pb-Zn ore bodies for validation.The results showed that the median+2 MAD approach is capable of mapping both strong and weak geochemical anomalies related to buried Pb-Zn mineralization,which is therefore useful at the reconnaissance drilling stage.

Spatial analysis for underground pipeline network information system

It is appropriate to establish underground pipeline network information system based on MapInfo software platform in many enterprises when taking account of the firm size and data amount. Since some functions of MapInfo in spatial analysis are not very strong relatively, it is difficult for MapInfo to fulfill some common functions about pipeline analysis such as spatial configuration, three-dimensional display, pipe exploding and so on. The thought and arithmetic to solve the above problems are approached based on respect theories of computer graphics and graph theory. A variety of function moduli have developed by means of senior computer languages and the system integration is realized.

Patent portfolio analysis model based on legal status information

Purpose:This research proposes a patent portfolio analysis model based on the legal status information to chart out a competitive landscape in a particular field,enabling organizations to position themselves within the overall technology landscape.Design/methodology/approach:Three indicators were selected for the proposed model:Patent grant rate,valid patents rate and patent maintenance period.The model uses legal status information to perform a qualitative evaluation of relative values of the individual patents,countries or regions’ technological capabilities and competitiveness of patent applicants.The results are visualized by a four-quadrant bubble chart To test the effectiveness of the model,it is used to present a competitive landscape in the lithium ion battery field.Findings:The model can be used to evaluate the values of the individual patents,highlight countries or regions’ positions in the field,and rank the competitiveness of patent applicants in the field.Research limitations:The model currently takes into consideration only three legal status indicators.It is actually feasible to introduce more indicators such as the reason for invalid patents and the distribution of patent maintenance time and associate them with those in the proposed model.Practical implications:Analysis of legal status information in combination of patent application information can help an organization to spot gaps in its patent claim coverage,as well as evaluate patent quality and maintenance situation of its granted patents.The study results can be used to support technology assessment,technology innovation and intellectual property management.Originality/value:Prior studies attempted to assess patent quality or competitiveness by using either single patent legal status indicator or comparative analysis of the impacts of each indicator.However,they are insufficient in presenting the combined effects of the evaluation indicators.Using our model,it appears possible to get a more complete and objective picture of the current competitive situation.