Reverse Engineering Methods Research Articles

Development of patient specific dental implant using 3D printing

In the last few years, the mixture of nuclear medicine and the reverse engineering method has confirmed to be an identical key development in the medical field. In contrast, the traditional method has some downsides. For instance, some difficulty presence in matching the well suitable due to the change of patient’s oral state and it takes more attention to meet reliability and comfort. So, the patient-specific prosthesis is required. An additional crucial problem of the patient-specific dental prosthesis is a fabrication method. The prosthesis in dental application is hard to fabricate owing to the multifaceted structures and base material. By the way of ever-growing demands for accuracy, complexity and skin-tight tolerance, traditional methods have turn into unsuccessful for machining them. This paper introduces a methodology for the computer-aided design and additive layer manufacturing of the patient-specific dental implant body for the rehabilitation of teeth. A 3Dimensional model of the dental imperfection is created while the acquirement of helical computed tomography scanning data. Then simulation is made over through software Carestream Dental. Finally, the implant is fixed into the patient’s tooth and the healing phase goes up to 3–6 months depending upon the patient. Then the crown is being fitted. During the healing phase to check the implant’s primary stability, implant stability quotient is checked. The values must be greater than or equal to 50 to attain primary stability. The medical practice exhibited that digital manufacturing and back-engineering software are outstanding mixtures of traits for dental devices designed to withstand tremendous masticatory forces and offer much more flexibility with the customized implant.

Mechanical Evaluation of Implant-Assisted Removable Partial Dentures in Kennedy Class I Patients: Finite Element Design Considerations

The main purpose of this work was to construct a clinically valid numerical model of a mandibular Kennedy class I patient rehabilitated with a conventional removable partial denture and another two with implant-assisted removable partial dentures at two different implant locations. The selected patient was classified as ASA I and its mandible geometry reconstruction was performed by the conversion of the Cone-Beam computed Tomography (CBCT) scan raw medical data into a 3D model and subsequent conversion to a CAD file by reverse engineering methods. The soft tissue and removable denture geometries were also included in the CAD model as well as implants, ball attachments and matrix. Moreover, periodontal ligament was modelled by offsetting the mesh of the root surface of each tooth. The finite element results showed that the installation of a dental implant in each of the bilateral edentulous regions helps providing support and retention to the extension bases of the Removable Partial Denture (RPD) and significantly reduces the vertical and anterior-posterior displacements, regardless of its position.

ARAZ: A software modules clustering method using the combination of particle swarm optimization and genetic algorithms

A considerable percentage of software costs are usually related to its maintenance. Program comprehension is a prerequisite of the software maintenance and a considerable time of maintainers is spent to comprehend the structure and behavior of the software when the source code is the only product available. Program comprehension is one of difficult and challenging task especially in the absence of design documents of the software system. Clustering of software modules is an effective reverse-engineering method for extracting the software architecture and structural model from the source code. Finding the best clustering is considered to be a multi-objective NP hard optimization-problem and different meta-heuristic algorithms have been used for solving this problem. Local optimum, insufficient quality, insufficient performance and insufficient stability are the main shortcomings of the previous methods. Attaining higher values for software clustering quality, attaining higher success rate in clustering of software modules, attaining higher stability of the obtained results and attaining the higher convergence (speed) to generate optimal clusters are the main goals of this study. In this study, a hybrid meta heuristic method (ARAZ) includes particle swarm optimization algorithm and genetic algorithm (PSO-GA) is proposed to find the best clustering of software modules. An extensive series of experiments on 10 standard benchmark programs have been conducted. Regarding the results of experiments, the proposed method outperforms the other methods in terms of clustering quality, stability, success rate and convergence speed.

WITHDRAWN: Protection android app with multiDEX and SO files from reverse engineering

Reverse engineering technique gives the attacker the gamble to embed the new code with apps; there is a chance of losing confidential information or adding some adware. Some most popular tool protects from reverse Engineering like LIAPP, IJIAMI, and ALIBABA, etc. Those tools can encrypt the DEX file in APK; before loading the files dynamically, it decrypts the files; the MultiDEX files do not defend these tools. We propose an approach to protect from reverse engineering methods. Our aim to protects against static repackaging attacks and provides better efficiency in decrypts and loading apps. We introduce the Virtual Machine (VM)-based MultiDEX and share object (SO) protection approach; we used the newly stack-based native code system in this approach. It provides intense level protection under the virtual machine. It leverages multiple dynamic virtual machines protection of bytecode to minimize the overhead. The significant advantage of our approach to protecting the MutiDex files and SO files is that very few systems are available, which take care of both types of files.

Forensic Recreation and Visual Representation of Greek Orthodox Church Saint Eftychios of Crete.

Facial reconstruction is employed in medical science and archaeology. Though quite popular as anthropological method, it has not so far been used in the orthodox ecclesiastical tradition. This work presents the facial reconstruction of St Eftychios of Crete, who lived between the ninth and tenth centuries. Computed tomography and reverse engineering methods were employed to complete the task. Reconstruction of the mandible and the missing left zygomatic arch was implemented following the Sassouni method. The American method was followed for the soft tissues, with clay deposition of appropriate thickness, on the surface of the skull model. The eyes, nose, and lips were added based on the dimensions of the underlying bone structures. Long hair and beard were added, according to the classic Byzantine tradition pattern of the time period. The final bust developed was then digitized, using a 3D non-contact laser scanner. The 3D geometry produced was employed to produce a mold with vacuum casting techniques. This mold provides the ability to produce copies of the bust, if needed. At the same time, a realistic 3D representation of the Saint's bust was developed, with the aid of special software, in order to compare the traditional forensic reconstruction to the pure digital one. This work is the first case of a Saint's facial reconstruction in the Orthodox Church. The facial reconstruction process, with all the limitations considered, offers the ability to present a realistic aspect of a Greek Orthodox Church Saint, in a form that is easily accessible. Both physical and digital facial reconstruction processes were based on scientific data, so they were as accurate as possible, considering that the mandible was missing in the skull. The facial reconstruction was entirely implemented in Greece creating the basis for similar work in the future. The final bust developed was donated to the Odigitria Monastery, to be exhibited to its visitors.

Development of comfort fit lower limb prosthesis by reverse engineering and rapid prototyping methods and validated with gait analysis

The development of comfort fit, custom made lower limb prosthesis using the concept of reverse engineering (RE) and rapid prototyping (RP) has been introduced in this paper. The comparison of average percentage of deviations in step lengths also made between normal people, the conventional (plaster of Paris - POP) prosthesis and reverse engineered rapid prototyping prosthesis through gait analysis. The gait analysis reveals that the average percentage of deviation in step lengths in normal person is 2.80, average percentage of deviation in step lengths in conventional (POP) prosthesis is 53.70 and reverse engineered rapid prototyping prosthesis is 7.06. The difference in average percentage of step lengths deviation between normal person and amputed person wearing reverse engineered and rapid prototyping prosthesis is very less (say 4.26) and hence provides comfort fit.

Development of comfort fit lower limb prosthesis by reverse engineering and rapid prototyping methods and validated with gait analysis

Development of comfort fit lower limb prosthesis by reverse engineering and rapid prototyping methods and validated with gait analysis

Model u prostoru problema nasleđenog sistema za podršku projektovanja i proizvodnje gumenih smeša

The fourth generation legacy system used for designing rubber compounds contains valuable information related to rules of business, knowledge, methods and results in compounding. In order to leverage the accumulated knowledge or design new applications related to compounding it is important to define a domain model based on the existing system used with remarkable success in the past twenty years. Due to the lack of both source and binary code, standard software reverse engineering methods could not be applied in this situation. In the process of manufacturing rubber products, the greatest attention is focused on a further understanding and improvement of the development of new rubber compound formulations, design technology and improvement of the existing ones. A basic problem that needs to be resolved is what kind of information is needed about a particular rubber compound. The problem of building an elastomer formulation from the ground up is complex and can easily entail thousands of choices by the compounder. This problem is not a trivial one, and it can only be resolved on the basis of available science-based elastomer technology as well as software engineering methods and models. Modelling in problem space is used as a research method in this paper. Model of problem space (MOPS) deals with creating and understanding of the problem, primarily the problem that a potential user of the system faces. The modelling output transcends both data and code and results in a suite of visual models or diagrams created with use of Unified Modelling Language (UML).

Race Cartels: How Constructor Collaboration Is Curbing Innovation in Formula 1

Formula 1 is in the midst of a copycat scandal: technology has made it possible for teams to reverse engineer clones of competitors’ race cars. This is a less than ideal state of affairs for the championship series, which prides itself on being the pinnacle of motorsport and automotive innovation, thanks in large part to the cars’ rapid rate of technological advancement. In order to address this problem, the Federation Internationale de l’Automobile (FIA), Formula 1’s governing body, must increase independent innovation efforts by amending the technical regulations to restrict the extent of presently allowed inter-team collaboration. Worried that the sport was becoming a “copying championship,” the FIA adopted new measures that ban extreme reverse engineering methods. Because these new FIA regulations do not limit the degree of coordinated conduct between teams, this approach will likely fail to remedy the sport’s copying problem because team plagiarism is an anticompetitive side effect of this collusive behavior. The FIA addresses the copying problem as one of trade secret misappropriation. By contrast, this Note approaches the issue as one of unregulated anticompetitive conduct. Analyzing the technical partnerships in Formula 1 under antitrust law elucidates their harmful effects on the racing series. This Note urges the FIA to adopt measures that limit Formula 1 teams’ ability to collaborate, before the “A-B team” phenomenon further diminishes the sport’s innovation efforts.

Feature Selection for Topological Proximity Prediction of Single-Cell Transcriptomic Profiles in Drosophila Embryo Using Genetic Algorithm

Single-cell transcriptomics data, when combined with in situ hybridization patterns of specific genes, can help in recovering the spatial information lost during cell isolation. Dialogue for Reverse Engineering Assessments and Methods (DREAM) consortium conducted a crowd-sourced competition known as DREAM Single Cell Transcriptomics Challenge (SCTC) to predict the masked locations of single cells from a set of 60, 40 and 20 genes out of 84 in situ gene patterns known in Drosophila embryo. We applied a genetic algorithm (GA) to predict the most important genes that carry positional and proximity information of the single-cell origins, in combination with the base distance mapping algorithm DistMap. Resulting gene selection was found to perform well and was ranked among top 10 in two of the three sub-challenges. However, the details of the method did not make it to the main challenge publication, due to an intricate aggregation ranking. In this work, we discuss the detailed implementation of GA and its post-challenge parameterization, with a view to identify potential areas where GA-based approaches of gene-set selection for topological association prediction may be improved, to be more effective. We believe this work provides additional insights into the feature-selection strategies and their relevance to single-cell similarity prediction and will form a strong addendum to the recently published work from the consortium.

Successive training of a generative adversarial network for the design of an optical cloak

At the nanoscale level, optical properties of materials depend greatly on their shape. Finding the right geometry for a specific property remains a fastidious and long task, even with the help of modelling tools. In this work, we overcome this challenge by using artificial intelligence to guide a reverse engineering method. We present an optimization algorithm based on a deep convolution generative adversarial network for the design a 2-dimensional optical cloak. The optical cloak consists in a shell of uniform and isotropical dielectric material, and the cloaking is achieved via the geometry of this shell. We use a feedback loop from the solutions of this generative network to successively retrain it and improve its ability to predict and find optimal geometries. This generative method allows to find a global solution to the optimization problem without any prior knowledge of good cloaking geometries.

AN IMPROVED DESIGN OF A SOYBEAN PEEL SEPARATOR FOR TEMPE PRODUCTION

Tempe is a typical food of Indonesia which is consumed by people throughout the world. Tempe is made of fermented soybean by Rhizopus sp. The production of tempe is labor intensive. Among the twelve core stages in tempe production. One of that is separating the peel of soybean which is performed by human energy. It is hard to make contamination-free tempe since manual operation is involved in the process. This research was conducted by reverse engineering method with the aim to redesign an existing soybean peeling separator base on the user needs. The cycle time of whole tempe production to detect the problem were calculated. The longest time is peel separating process which use 40% from the whole tempe production. This station will be examined deeply an calculated per work elements and classify these elements to be the criterion of the developed machine. These criterion generate various design concepts, then each design will be chosen using scoring concept, screening concept, and feasibility to be realized. The results revealed that, the newly designed peel separator decreased the processing time by 39%, which decrease the risk of contamination by manual operator. In addition to that, the reduction of cycle time was decreased the water and electricity use of tempe production.

Finite element validation of 3D American football faceguard structural stiffness models

Despite continued efforts to improve American football headgear technology, minimal structural changes have been made to faceguard design in the past 20 years. Although each new helmet system has its own compatible faceguard series, the primary design components have changed little between helmet systems. Additionally, little is known about specific parameters that influence faceguard performance, largely due to the variation inherent in laboratory impact testing. The goal of this study was two-fold: to validate a reverse engineering method for developing a library of faceguard models; and to validate the finite element simulation of three common American football faceguards subject to a quasi-static structural stiffness test. Three common Riddell® Speedflex™ (Des Plaines, IL) faceguard styles were modeled using a novel reverse engineering approach. Within ANSYS® Mechanical™ (ANSYS, Inc., Canonsburg, PA), the faceguards were modeled as stainless steel (elastic modulus = 193 GPa, Poisson’s ratio = 0.31). A displacement of 5 mm was prescribed in the posterior (z) direction. Boundary conditions were applied to accommodate the coronal plane (x, y) translation at clip attachment locations. The computational results correlated to the experimental results with statistical significance ( p value = 0.001). The Nose location was the most reliable with an average percent difference from experimental results of 2.7%, compared to 10.8% and 9.9% at the Mouth and Chin locations, respectively. Many studies utilizing computational models of protective headgear lack reported validation of headgear components. This study has validated the structural stiffness of three common faceguards to be used in future computational analyses. Furthermore, advancements in additive manufacturing technologies have opened the door to increasingly complex faceguard design capabilities; however, little is known about specific parameters that influence faceguard performance. With the models validated in this study, parameterized faceguard models should be used to iterate between design variables and assess the contribution of each variable on faceguard structural stiffness.

Design of simulation tools hybrid transmission mechanism

Simulation tool is a learning facility that presents learning experiences using artificial situations or system models so that one can understand certain concepts. This design aims to create a simulation tool as a learning media for planetary gear mechanisms in hybrid transmission systems. The method used in the design uses the reverse engineering method which is focused on the mechanism of the planetary gear, so that it can be made into a simulation tool. The planetary gear component design are based on data from Toyota Prius reference system using a torque ratio, with planning power of 15 kW and a rotation of 300 r/min. The planetary gear system consists of a sun gear with a diameter of 75 mm and 25 pieces of teeth, a planetary gear with a diameter of 54 mm and 17 pieces of teeth, and a ring gear with a diameter of 18 mm and 60 pieces of teeth. The result of design shows that the hybrid transmission simulation tool mechanism can function well as a learning medium with variations of 3 outputs.

Development of leaf spring design in large vehicles made from material type 65 si7 using static analysis with reverse engineering

University of Indonesia Electric Bus was first developed using Hino R260 chassis. For further development, especially to fill out local content, it must be carried out engineering of its components. One of which will be discussed in this paper is the spring component. Reverse Engineering method is used to redesign in such a way. Measurement of the existing leaf springs in the chassis is done. The dimensions and number of leaf springs for the front and rear wheels of the chassis are produced. With CAD software and finite element analysis, a static analysis is performed on each of these springs. Front axle leaf spring arrangement consists of 8 spring sheets with dimensions of width 80 mm and thickness of 10 mm with stratified length. Rear axle leaf spring arrangement consists of 5 spring springs with dimensions of 90 mm width and 12 mm thickness with evenly distributed length. The theoretical stress on the front leaf springs is 512.74 MPa and finite element analysis is 531.5 MPa. The theoretical stress behind the leaf spring which occurs is 721.67 MPa and elemental analysis up to 728.4 MPa. The material for both of these springs is chosen is 65 si7 or SUP9.

Improving the Quality of Coffee Shops in Jabodetabek Area by Application and Modification of Coffee Roaster Machine Capacity 400-600 Gram Coffee Beans Using the Reverse Engineering and Engineering Design Method

Coffee roaster machine or commonly called coffee roaster is a tool for cooking coffee beans that have been fermented during the process of cherry coffee into coffee beans in a measured and controlled manner. Coffee shops have constraints in fulfilling the ingredients of the coffee beans themselves by using a roaster coffee machine available at the market less 400 grams or bigger then 1000grams, so that does not match with the needs of the limited ingredients of coffee beans, the coffee shop buys cooked coffee beans at a more expensive price. Therefore, in this research a coffee roaster machine will be designed at the capacity of 400 grams up to 600 grams. Reverse Engineering is a process of analyzing existing products or machine as a reference for designing similar products by minimizing and increasing an excellence product. Reverse Engineering activities have carried out by dismantling and replacing the old coffee roaster. Engineering Designing a new roaster machine, and the last is built a prototype machine. The new design of a roaster machine can produce a faster roasted coffee with the capacity between 400 grams up to 600 grams/77 minutes, in the process of roasting coffee with additional in weight of 200 grams of coffee in a roasted coffee machine after modification.

Modern Reverse Engineering Methods Used to Modification of Jewelry

Modern Reverse Engineering Methods Used to Modification of Jewelry

Protocol format extraction based on an improved CFSM algorithm

As the information technology rapidly develops, many network applications appear and their communication protocols are unknown. Although many protocol keyword recognition based protocol reverse engineering methods have been proposed, most of the keyword recognition algorithms are time consuming. This paper firstly uses the traffic clustering method F-DBSCAN to cluster the unknown protocol traffic. Then an improved CFSM (Closed Frequent Sequence Mining) algorithm is used to mine closed frequent sequences from the messages and identify protocol keywords. Finally, CFGM (Closed Frequent Group Mining) algorithm is proposed to explore the parallel, sequential and hierarchical relations between the protocol keywords and obtain accurate protocol message formats. Experimental results show that the proposed protocol formats extraction method is better than Apriori algorithm and Sequence alignment algorithm in terms of time complexity and it can achieve high keyword recognition accuracy. Additionally, based on the relations between the keywords, the method can obtain accurate protocol formats. Compared with the protocol formats obtained from the existing methods, our protocol format can better grasp the overall structure of target protocols and the results perform better in the application of protocol reverse engineering such as fuzzing test.

Robust Kirchhoff transformation using B-spline for finite element analysis of the non-linear heat conduction

For non-linear problems, the solution of the heat equation in terms of the Kirchhoff transformation, θ(T), is very limited. This restriction is due to the practical disadvantage of the inverse temperature shift from the Kirchhoff transform T(θ). In order to get around the difficulties associated with the representation of θ(T) and its inverse T(θ) for solids with strongly non-linear conductivities, a strategy based on a reverse engineering method is considered. It consists in identifying the number of knots and their respective locations on the curve T(θ) at the most efficient computational cost. In order to obtain the location of the knots, the curve is fitted by B-spline functions and the data is partitioned by an application of the bisectional method with a predetermined error. These knots are further optimized using the non-linear least squares method. The proposed approach can be combined with a numerical method such as the FEM, BEM, and FEV to provide the non-linear solution of the heat equation in terms of θ. However, in this work we have limited ourselves to the FEM. The validation of the proposed approach is achieved through several cases ranging from constant to strongly non-linear thermal conductivities with or without convection. As an application, the 3D finite element method is applied to determine the non-linear temperature distribution in a copper block with an imposed temperature.

Network Survival Strategies of Migrant Entrepreneurs in Large Cities: Analysis of Albanian Firms in Milan

ABSTRACT This paper addresses the role of cultural bias (preference for what is culturally more akin) in the entrepreneurial choice regarding different types of social networks in the context of urban mixed embeddedness. We test empirically the presence and aftermaths of this cultural bias, drawing on evidence from a natural experiment with regard to Albanian ethnic entrepreneurs in the city of Milan, Italy. Namely, these entrepreneurs are exposed to the same mixed urban embeddedness and, when we control for firm characteristics, the only discriminating component explaining their success is their choice of social network. We focus on the choice over three types of social networks, classified according to varying degrees of cultural distance between the network and the entrepreneur: (a) the indigenous population, (b) the local Albanian diaspora, and (c) fellow citizens residing in the country of origin, Albania (i.e., transnational networking). We employ a novel method for reverse engineering of preferences for networking by using a Kaplan-Meier estimator and a propensity-score matching technique. We find that strategic network liaisons with locals is actually the most beneficial social network for ethnic firm performance. However, it is social networking within the culturally closer local Albanian diaspora that is the most common behaviour.