Search results for: precision of gearing

Authors: Mehdi Ameur, Ahmed Essadki, Tamou Nasser

Abstract:

The purpose of this paper is the evaluation of photovoltaic system with MPPT techniques. This system is developed by combining the models of established solar module and DC-DC converter with the algorithms of perturbing and observing (P&O), incremental conductance (INC) and fuzzy logic controller (FLC). The system is simulated under different climate conditions and MPPT algorithms to determine the influence of these conditions on characteristic power-voltage of PV system. According to the comparisons of the simulation results, the photovoltaic system can extract the maximum power with precision and rapidity using the MPPT algorithms discussed in this paper.

Keywords: fuzzy logic controller, FLC, hill climbing, HC, incremental conductance (INC), perturb and observe (P&O), maximum power point, MPP, maximum power point tracking, MPPT

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Authors: Minghui Zhang, Sirine Fkaier, Sabri Fernana, Svetlana Kiseleva, Denis Kiselev

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The real-time identification of bacteria and fungi is difficult because they emit much weaker signals than pollen. In 2020, Plair developed Rapid-E+, which extends abilities of Rapid-E to detect smaller bioaerosols such as bacteria and fungal spores with diameters down to 0.3 µm, while keeping the similar or even better capability for measurements of large bioaerosols like pollen. Rapid-E+ enables simultaneous measurements of (1) time-resolved, polarization and angle dependent Mie scattering patterns, (2) fluorescence spectra resolved in 16 channels, and (3) fluorescence lifetime of individual particles. Moreover, (4) it provides 2D Mie scattering images which give the full information on particle morphology. The parameters of every single bioaerosol aspired into the instrument are subsequently analysed by machine learning. Firstly, pure species of microbes, e.g., Bacillus subtilis (a species of bacteria), and Penicillium chrysogenum (a species of fungal spores), were aerosolized in a bioaerosol chamber for Rapid-E+ training. Afterwards, we tested microbes under different concentrations. We used several steps of data analysis to classify and identify microbes. All single particles were analysed by the parameters of light scattering and fluorescence in the following steps. (1) They were treated with a smart filter block to get rid of non-microbes. (2) By classification algorithm, we verified the filtered particles were microbes based on the calibration data. (3) The probability threshold (defined by the user) step provides the probability of being microbes ranging from 0 to 100%. We demonstrate how Rapid-E+ identified simultaneously microbes based on the results of Bacillus subtilis (bacteria) and Penicillium chrysogenum (fungal spores). By using machine learning, Rapid-E+ achieved identification precision of 99% against the background. The further classification suggests the precision of 87% and 89% for Bacillus subtilis and Penicillium chrysogenum, respectively. The developed algorithm was subsequently used to evaluate the performance of microbe classification and quantification in real-time. The bacteria and fungi were aerosolized again in the chamber with different concentrations. Rapid-E+ can classify different types of microbes and then quantify them in real-time. Rapid-E+ enables classifying different types of microbes and quantifying them in real-time. Rapid-E+ can identify pollen down to species with similar or even better performance than the previous version (Rapid-E). Therefore, Rapid-E+ is an all-in-one instrument which classifies and quantifies not only pollen, but also bacteria and fungi. Based on the machine learning platform, the user can further develop proprietary algorithms for specific microbes (e.g., virus aerosols) and other aerosols (e.g., combustion-related particles that contain polycyclic aromatic hydrocarbons).

Keywords: bioaerosols, laser-induced fluorescence, Mie-scattering, microorganisms

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Authors: Satyanarayana Kosaraju, Venu Gopal Anne, Sateesh Nagari

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In this paper, the effect of cutting speed, feedrate and rake angle in tool geometry on cutting forces and temperature generated on the tool tip in turning were investigated. The data used for the investigation derived from experiments conducted on precision lathe according to the full factorial design to observe the effect of each factor level on the process performance. During the tests, depth of cut were kept constant and each test was conducted with a sharp coated tool insert. Ti-6Al-4V was used as the workpiece material. The effects of cutting parameters and tool geometry on cutting forces and tool tip temperature were analyzed. The main cutting force was observed to have a decreasing trend and temperature found to be increasing trend as the rake angle increased.

Keywords: cutting force, tool tip temperature, rake angle, machining

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Authors: Takashi Sakai, Itaru Kumisawa

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Because die drawing requires insertion of a die, a plug, or a mandrel, higher precision and efficiency are demanded for drawing equipment for a tube having smaller diameter. Manufacturing of such tubes is also accompanied by problems such as cracking and fracture. We specifically examine dieless drawing, which is less affected by these drawing-related difficulties. This deformation process is governed by a similar principle to that of reduction in diameter when pulling a heated glass tube. We conducted dieless drawing of SUS304 stainless steel microtubes under various conditions with three factor parameters of heating temperature, area reduction, and drawing speed. We used SEM-EBSD to observe the processing condition effects on microstructural elements. As the result of this study, crystallographic orientation of microtube is clear by using SEM-EBSD analysis.

Keywords: microtube, dieless drawing, IPF (inverse pole figure), GOS (grain orientation spread), crystallographic analysis

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Authors: Nada Farhani, Naim Terbeh, Mounir Zrigui

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The recognition of the objects contained in images has always presented a challenge in the field of research because of several difficulties that the researcher can envisage because of the variability of shape, position, contrast of objects, etc. In this paper, we will be interested in the recognition of objects. The classical Hough Transform (HT) presented a tool for detecting straight line segments in images. The technique of HT has been generalized (GHT) for the detection of arbitrary forms. With GHT, the forms sought are not necessarily defined analytically but rather by a particular silhouette. For more precision, we proposed to combine the results from the GHT with the results from a calculation of similarity between the histograms and the spatiograms of the images. The main purpose of our work is to use the concepts from recognition to generate sentences in Arabic that summarize the content of the image.

Keywords: recognition of shape, generalized hough transformation, histogram, spatiogram, learning

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Authors: Maria Fernanda Ordoñez Martinez, Alvaro Mauricio Montenegro

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This work presents a statistical methodology for measuring and founding constructs in Latent Semantic Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations present on Item Response Theory. More precisely, we propose initially reducing dimensionality with specific use of Principal Component Analysis for the linguistic data and then, producing axes of groups made from a clustering analysis of the semantic data. This approach allows the user to give meaning to previous clusters and found the real latent structure presented by data. The methodology is applied in a set of real semantic data presenting impressive results for the coherence, speed and precision.

Keywords: semantic analysis, factorial analysis, dimension reduction, penalized logistic regression

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Authors: Bernd Kiefer, Abraham Gebru Tesfay, Dietrich Klakow

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The motivation of our work is to detect different terrain types traversed by a robot based on acoustic data from the robot-terrain interaction. Different acoustic features and classifiers were investigated, such as Mel-frequency cepstral coefficient and Gamma-tone frequency cepstral coefficient for the feature extraction, and Gaussian mixture model and Feed forward neural network for the classification. We analyze the system’s performance by comparing our proposed techniques with some other features surveyed from distinct related works. We achieve precision and recall values between 87% and 100% per class, and an average accuracy at 95.2%. We also study the effect of varying audio chunk size in the application phase of the models and find only a mild impact on performance.

Keywords: acoustic features, autonomous robots, feature extraction, terrain classification

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Authors: Ramandeep Behl, S. S. Motsa

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The main focus of this manuscript is to provide a highly efficient two-point sixth-order family of super-Halley type methods that do not require any second-order derivative evaluation for obtaining simple roots of nonlinear equations, numerically. Each member of the proposed family requires two evaluations of the given function and two evaluations of the first-order derivative per iteration. By using Mathematica-9 with its high precision compatibility, a variety of concrete numerical experiments and relevant results are extensively treated to confirm t he t heoretical d evelopment. From their basins of attraction, it has been observed that the proposed methods have better stability and robustness as compared to the other sixth-order methods available in the literature.

Keywords: basins of attraction, nonlinear equations, simple roots, super-Halley

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Authors: Prajwal Prakash Vasisht, Sharath Rajamurthy, Nishanth Dara

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In a supervised machine learning approach, metrics such as precision, accuracy, and coverage can be calculated using ground truth labels to help in model tuning, evaluation, and selection. In an unsupervised setting, however, where the data has no ground truth, there are few interpretable metrics that can guide us to do the same. Our approach creates a framework to adapt the Intersection over Union metric, referred to as Adapted IoU, usually used to evaluate supervised learning models, into the unsupervised domain, which solves the problem by factoring in subject matter expertise and intuition about the ideal output from the model. This metric essentially provides a scale that allows us to compare the performance across numerous unsupervised models or tune hyper-parameters and compare different versions of the same model.

Keywords: general metric, unsupervised learning, classification, intersection over union

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Authors: Labane Chrif

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A nonlinear approach to the automatic pitch attitude control problem for aircraft transportation is presented. A nonlinear model describing the longitudinal equations of motion in strict feedback form is derived. Backstepping is utilized for the construction of a globally stabilizing controller with a number of free design parameters. The controller is evaluated using the aircraft transportation. The adaptation scheme proposed allowed us to design an explicit controller with a minimal knowledge of the aircraft aerodynamics. Finally, the simulation results will show that backstepping controller have better dynamic performance, simpler design, higher precision, easier implement, etc. At the same time, the control effect will be significantly improved. In addition, backstepping control is superior in short transition, good stability, anti-disturbance and good control.

Keywords: nonlinear control, backstepping, aircraft control, Lyapunov function, longitudinal model

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Authors: Siavash Eftekharifar, Tohid Yousefi Rezaii, Mahdi Shamsi

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The purpose of this paper is to exploit compressed sensing (CS) method in order to model and compress the electrocardiogram (ECG) signals at a high compression ratio. In order to obtain a sparse representation of the ECG signals, first a suitable basis matrix with Gaussian kernels, which are shown to nicely fit the ECG signals, is constructed. Then the sparse model is extracted by applying some optimization technique. Finally, the CS theory is utilized to obtain a compressed version of the sparse signal. Reconstruction of the ECG signal from the compressed version is also done to prove the reliability of the algorithm. At this stage, a greedy optimization technique is used to reconstruct the ECG signal and the Mean Square Error (MSE) is calculated to evaluate the precision of the proposed compression method.

Keywords: compressed sensing, ECG compression, Gaussian kernel, sparse representation

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Authors: Jihen Bennaceur, Wissem Zouaghi, Ali Mabrouk

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The major aim of cyber threat intelligence (CTI) is to provide sophisticated knowledge about cybersecurity threats to ensure internal and external safeguards against modern cyberattacks. Inaccurate, incomplete, outdated, and invaluable threat intelligence is the main problem. Therefore, data analysis based on AI algorithms is one of the emergent solutions to overcome the threat of information-sharing issues. In this paper, we propose a supervised machine learning-based algorithm to improve threat information sharing by providing a sophisticated classification of cyber threats and data. Extensive simulations investigate the accuracy, precision, recall, f1-score, and support overall to validate the designed algorithm and to compare it with several supervised machine learning algorithms.

Keywords: threat information sharing, supervised learning, data classification, performance evaluation

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Authors: El Hansali Hasnaa, Bennani Mohammed

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Hexapod legged robot’s missions, particularly in irregular and dangerous areas, require high stability and high precision. In this paper, we consider the rectangular architecture body of legged robots with six legs distributed symmetrically along two sides, each leg contains three degrees of freedom for greater mobility. The aim of this work is planning tripod gait trajectory, based on the computing of the kinematic model to determine the joint variables in the lifting and the propelling phases. For this, appropriate coordinate frames are attached to the body and legs in order to obtain clear representation and efficient generation of the system equations. A simulation in MATLAB software platform is developed to confirm the kinematic model and various trajectories to the tripod gait adopted by the hexapod robot in its locomotion.

Keywords: hexapod legged robot, inverse kinematic model, simulation in MATLAB, tripod gait

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Authors: Tahisa M. Pedroso, Hérida R. N. Salgado

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The microbiological turbidimetric assay allows the determination of potency of the drug, by measuring the turbidity (absorbance), caused by inhibition of microorganisms by ertapenem sodium. Ertapenem sodium (ERTM), a synthetic antimicrobial agent of the class of carbapenems, shows action against Gram-negative, Gram-positive, aerobic and anaerobic microorganisms. Turbidimetric assays are described in the literature for some antibiotics, but this method is not described for ertapenem. The objective of the present study was to develop and validate a simple, sensitive, precise and accurate microbiological assay by turbidimetry to quantify ertapenem sodium injectable as an alternative to the physicochemical methods described in the literature. Several preliminary tests were performed to choose the following parameters: Staphylococcus aureus ATCC 25923, IAL 1851, 8 % of inoculum, BHI culture medium, and aqueous solution of ertapenem sodium. 10.0 mL of sterile BHI culture medium were distributed in 20 tubes. 0.2 mL of solutions (standard and test), were added in tube, respectively S1, S2 and S3, and T1, T2 and T3, 0.8 mL of culture medium inoculated were transferred to each tube, according parallel lines 3 x 3 test. The tubes were incubated in shaker Marconi MA 420 at a temperature of 35.0 °C ± 2.0 °C for 4 hours. After this period, the growth of microorganisms was inhibited by addition of 0.5 mL of 12% formaldehyde solution in each tube. The absorbance was determined in Quimis Q-798DRM spectrophotometer at a wavelength of 530 nm. An analytical curve was constructed to obtain the equation of the line by the least-squares method and the linearity and parallelism was detected by ANOVA. The specificity of the method was proven by comparing the response obtained for the standard and the finished product. The precision was checked by testing the determination of ertapenem sodium in three days. The accuracy was determined by recovery test. The robustness was determined by comparing the results obtained by varying wavelength, brand of culture medium and volume of culture medium in the tubes. Statistical analysis showed that there is no deviation from linearity in the analytical curves of standard and test samples. The correlation coefficients were 0.9996 and 0.9998 for the standard and test samples, respectively. The specificity was confirmed by comparing the absorbance of the reference substance and test samples. The values obtained for intraday, interday and between analyst precision were 1.25%; 0.26%, 0.15% respectively. The amount of ertapenem sodium present in the samples analyzed, 99.87%, is consistent. The accuracy was proven by the recovery test, with value of 98.20%. The parameters varied did not affect the analysis of ertapenem sodium, confirming the robustness of this method. The turbidimetric assay is more versatile, faster and easier to apply than agar diffusion assay. The method is simple, rapid and accurate and can be used in routine analysis of quality control of formulations containing ertapenem sodium.

Keywords: ertapenem sodium, turbidimetric assay, quality control, validation

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Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long

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In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.

Keywords: agricultural object detection, deep learning, machine vision, YOLO family

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Authors: Mareye Zeleke Mekonen

Abstract:

The Kafficho language has distinct issues in information retrieval because of its restricted resources and dearth of standardized methods. In this endeavor, with the cooperation and support of linguists and native speakers, we investigate the creation of information retrieval systems specifically designed for the Kafficho language. The Kafficho information retrieval system allows Kafficho speakers to access information easily in an efficient and effective way. Our objective is to conduct an information retrieval experiment using 220 Kafficho text files, including fifteen sample questions. Tokenization, normalization, stop word removal, stemming, and other data pre-processing chores, together with additional tasks like term weighting, were prerequisites for the vector space model to represent each page and a particular query. The three well-known measurement metrics we used for our word were Precision, Recall, and and F-measure, with values of 87%, 28%, and 35%, respectively. This demonstrates how well the Kaffiho information retrieval system performed well while utilizing the vector space paradigm.

Keywords: Kafficho, information retrieval, stemming, vector space

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Authors: R. Trad Khodja, A. Guessmi, R. Ghoul, A. Mahtout, S. A. Benbouali, M. A. Boulahlib

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Cranioplasty is a surgical act that aims to restore cranial bone losses in order to protect the brain from external aggressions and to improve the patient's aesthetic appearance. This objective can be achieved by taking advantage of the current technological development in computer science and biomechanics. The objective of this paper is to present an approach for the realization of high-precision biocompatible cranial implants using new 3D printing technologies at the lowest cost. The proposed method is to reproduce the missing part of the skull by referring to its healthy contralateral part. Once the model is validated by the neurosurgeons, a mold is 3D printed for the production of a biocompatible implant in Poly-Methyl-Methacrylate (PMMA) acrylic cement. Using this procedure, ten patients underwent this procedure with excellent aesthetic results.

Keywords: cranioplasty, cranial defect, PMMA, 3d printing, custom made implants

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Authors: Benchalak Muangmeesri

Abstract:

Glazes ceramics are ceramic materials produced through controlled crystallization of a parent glass. The great variety of compositions and the possibility of developing special micro structures with specific technological properties have allowed glass ceramic materials to be used in a wide range of applications. At the same time, glazes ceramics need to improvement in the mechanical and chemical properties of glazed. The pick and place station is equipped with a three-axis module. test piece housings placed on the vacuum are detected module picks up a test piece insert from the slide and places it on the test piece housing. Overall, glazes ceramics are compared with automatically and manually of speed and position control. The handling modules of automatic transfer are a new generation of high speed and precision then these color results from absorption and thickness than manual is also included.

Keywords: glaze, PID control, pick and place, ceramic

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Authors: Mehdi Ameur, Ahmed Essakdi, Tamou Nasser

Abstract:

The purpose of this paper is the analysis and modeling of the photovoltaic system with MPPT techniques. This system is developed by combining the models of established solar module and DC-DC converter with the algorithms of perturb and observe (P&O), incremental conductance (INC) and fuzzy logic controller(FLC). The system is simulated under different climate conditions and MPPT algorithms to determine the influence of these conditions on characteristic power-voltage of PV system. According to the comparisons of the simulation results, the photovoltaic system can extract the maximum power with precision and rapidity using the MPPT algorithms discussed in this paper.

Keywords: photovoltaic array, maximum power point tracking, MPPT, perturb and observe, P&O, incremental conductance, INC, hill climbing, HC, fuzzy logic controller, FLC

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Authors: Nevena Jakovčević Stor, Ivan Slapničar

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Any polynomial can be expressed as a characteristic polynomial of a complex symmetric arrowhead matrix. This expression is not unique. If the polynomial is real with only real distinct roots, the matrix can be chosen as real. By using accurate forward stable algorithm for computing eigen values of real symmetric arrowhead matrices we derive a forward stable algorithm for computation of roots of such polynomials in O(n^2 ) operations. The algorithm computes each root to almost full accuracy. In some cases, the algorithm invokes extended precision routines, but only in the non-iterative part. Our examples include numerically difficult problems, like the well-known Wilkinson’s polynomials. Our algorithm compares favorably to other method for polynomial root-finding, like MPSolve or Newton’s method.

Keywords: roots of polynomials, eigenvalue decomposition, arrowhead matrix, high relative accuracy

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Authors: M. T. Ahn, J. H. Park, S. H. Park, S. H. Ha

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Diffusion bonding has been continuously studied. Temperature and pressure are the most important factors to increase the strength between diffusion bonded interfaces. Diffusion bonding is an important factor affecting the bonding strength of the lined pipe. The increase of the diffusion bonding force results in a high formability clad pipe. However, in the case of drawing, it is difficult to obtain a high pressure between materials due to a relatively small reduction in cross-section, and it is difficult to prevent elongation or to tear of material in hot drawing even if the reduction in the section is increased. In this paper, to increase the diffusion bonding force, we derive optimal temperature and pressure to suppress material stretching and realize precise thickness precision.

Keywords: diffusion bonding, temperature, pressure, drawing speed

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: emotion detection, TF-IDF, WEKA tool, classification algorithms

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Authors: Po-Hao Huang, Pei-Ju Chiang

Abstract:

The structured light 3D scanner is commonly used for measuring the 3D shape of an object. Through projecting designed light patterns on the object, deformed patterns can be obtained and used for the geometric shape reconstruction. At present, Gray code is the most reliable and commonly used light pattern in the structured light 3D scanner. However, the trade-off between scanning efficiency and accuracy is a long-standing and challenging problem. The design of light patterns plays a significant role in the scanning efficiency and accuracy. Thereby, we proposed a novel encoding method integrating color information and Gray-code to improve the scanning efficiency. We will demonstrate that with the proposed method, the scanning time can be reduced to approximate half of the one needed by Gray-code without reduction of precision.

Keywords: gray-code, structured light scanner, 3D shape acquisition, 3D reconstruction

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Authors: Albert K. Chong, Jasim Ahmed Ali Al-Baghdadi, Peter B. Milburn

Abstract:

Precise capture of plantar 3D surface of the foot at the loading gait phases on rigid substrate was found to be valuable for the assessment of the physiology, health and problems of the feet. Photogrammetry, a precision 3D spatial data capture technique is suitable for this type of dynamic application. In this research, the technique is utilised to study of the effect on the plantar deformation for having a strip of kinesiology tape on the plantar surface while going through the loading phase of gait. For this pilot study, one healthy adult male subject was recruited under the USQ University human research ethics guidelines for this preliminary study. The 3D plantar deformation data of both with and without applying the tape were analysed. The results and analyses are presented together with the detail of the findings.

Keywords: gait, human plantar, plantar loading, photogrammetry, kinesiology tape

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Authors: A. El Kachani, E. Chakir, A. Ait Laachir, A. Niaaniaa, J. Zerouaoui

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This document presents an adaptive controller based on recursive parametric identification applied to a wind turbine based on the doubly-fed induction machine (DFIG), to compensate the faults and guarantee efficient of the DFIG. The proposed adaptive controller is based on the recursive least square algorithm which considers that the best estimator for the vector parameter is the vector x minimizing a quadratic criterion. Furthermore, this method can improve the rapidity and precision of the controller based on a model. The proposed controller is validated via simulation on a 5.5 kW DFIG-based wind turbine. The results obtained seem to be good. In addition, they show the advantages of an adaptive controller based on recursive least square algorithm.

Keywords: adaptive controller, recursive least squares algorithm, wind turbine, doubly fed induction generator

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Authors: C. Benjbara, A. Habbani

Abstract:

Wireless networks are getting more and more used in every new technology or feature, especially those without infrastructure (Ad hoc mode) which provide a low cost alternative to the infrastructure mode wireless networks and a great flexibility for application domains such as environmental monitoring, smart cities, precision agriculture, and so on. These application domains present a common characteristic which is the need of coexistence and intercommunication between modules belonging to different types of ad hoc networks like wireless sensor networks, mesh networks, mobile ad hoc networks, vehicular ad hoc networks, etc. This vision to bring to life such heterogeneous networks will make humanity duties easier but its development path is full of challenges. One of these challenges is the communication complexity between its components due to the lack of common or compatible protocols standard. This article proposes a new patented routing protocol based on the OLSR standard in order to resolve the heterogeneous ad hoc networks communication issue. This new protocol is applied on a specific network architecture composed of MANET, VANET, and FANET.

Keywords: Ad hoc, heterogeneous, ID-Node, OLSR

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Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.

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Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.

Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine

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Authors: A. Ikusika, O. I. Poppola

Abstract:

This study was carried out to delineate possible structures that may favour the accumulation of tantalite, a magnetic mineral. A ground based technique was employed using proton precision magnetometer G-856 AX. A total of ten geophysical traverses were established in the study area. The acquired magnetic field data were corrected for drift. The trend analysis was adopted to remove the regional gradient from the observed data and the resulting results were presented as profiles. Quantitative interpretation only was adopted to obtain the depth to basement using Peter half slope method. From the geological setting of the area and the information obtained from the magnetic survey, a conclusion can be made that the study area is underlain by a rock unit of accumulated minerals. It is therefore suspected that the overburden is relatively thin within the study area and the metallic minerals are in disseminated quantity and at a shallow depth.

Keywords: basement, drift, magnetic field data, tantalite, traverses

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Authors: Michal Lysek, Mike Danilovic, Jasmine Lihua Liu

Abstract:

HMS Industrial Networks AB has been recognized as one of the most innovative companies in the industrial communication industry worldwide. The creation of their Anybus innovation during the 1990s contributed considerably to the company’s success. From inception, HMS’ employees were innovating for the purpose of creating new business (the creation phase). After the Anybus innovation, they began the process of internationalization (the commercialization phase), which in turn led them to concentrate on cost reduction, product quality, delivery precision, operational efficiency, and increasing growth (the growth phase). As a result of this transformation, performing new radical innovations have become more complicated. The purpose of our research was to explore the dynamics of innovation at HMS from the aspect of key actors, activities, and events, over the three phases, in order to understand what led to the creation of their Anybus innovation, and why it has become increasingly challenging for HMS to create new radical innovations for the future. Our research methodology was based on a longitudinal, retrospective study from the inception of HMS in 1988 to 2014, a single case study inspired by the grounded theory approach. We conducted 47 interviews and collected 1 024 historical documents for our research. Our analysis has revealed that HMS’ success in creating the Anybus, and developing a successful business around the innovation, was based on three main capabilities – cultivating customer relations on different managerial and organizational levels, inspiring business relations, and balancing complementary human assets for the purpose of business creation. The success of HMS has turned the management’s attention away from past activities of key actors, of their behavior, and how they influenced and stimulated the creation of radical innovations. Nowadays, they are rhetorically focusing on creativity and innovation. All the while, their real actions put emphasis on growth, cost reduction, product quality, delivery precision, operational efficiency, and moneymaking. In the process of becoming an international company, HMS gradually refocused. In so doing they became profitable and successful, but they also forgot what made them innovative in the first place. Fortunately, HMS’ management has come to realize that this is the case and they are now in search of recapturing innovation once again. Our analysis indicates that HMS’ management is facing several barriers to innovation related path dependency and other lock-in phenomena. HMS’ management has been captured, trapped in their mindset and actions, by the success of the past. But now their future has to be secured, and they have come to realize that moneymaking is not everything. In recent years, HMS’ management have begun to search for innovation once more, in order to recapture their past capabilities for creating radical innovations. In order to unlock their managerial perceptions of customer needs and their counter-innovation driven activities and events, to utilize the full potential of their employees and capture the innovation opportunity for the future.

Keywords: barriers to innovation, dynamics of innovation, in search of excellence and innovation, radical innovation

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Authors: Jiahe Liu, Hongyang Yu, Miao Luo, Feng Qian

Abstract:

The widespread application of 3D human body reconstruction spans various fields. Smplify-X, an algorithm reliant on single-image input, employs three distinct body parameter templates, necessitating gender classification of individuals within the input image. Researchers employed a ResNet18 network to train a gender classifier within the Smplify-X framework, setting the threshold at 0.9, designating images falling below this threshold as having neutral gender. This model achieved 62.38% accurate predictions and 7.54% incorrect predictions. Our improvement involved refining the MobileNet network, resulting in a raised threshold of 0.97. Consequently, we attained 78.89% accurate predictions and a mere 0.2% incorrect predictions, markedly enhancing prediction precision and enabling more precise 3D human body reconstruction.

Keywords: SMPLX, mobileNet, gender classification, 3D human reconstruction

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