Hasil untuk "Management. Industrial management"

I. S. Baird, H. Thomas

A model of strategic risk taking incorporating environmental, industrial, organizational, decision maker, and problem variables is presented. The model is intended to be both a preliminary conceptualization of strategic risk taking and a stimulant for future research on risk taking in strategic management decisions. Relevant research from a number of disciplines is summarized, and the potential impacts of particular variables on the propensity to take strategic risks are examined.

M. Lubatkin

Asadullah Shaikh, Wahidur Rahman, Kaniz Roksana et al.

Bangladesh has plentiful water, which is essential to its freshwater fish traditions. Environmental concerns and other causes have reduced the country's water resources, threatening many native freshwater fish species. Thus, the younger generation deficiencies recognition of local freshwater fish and struggles to recognize them. Traditional methods are very insufficient to overcome these issues. To address these research gaps, the research proposes an automatic system for categorizing Bangladesh's freshwater fish. The proposed methodology involves several key steps, including building a comprehensive dataset, extracting features from fish images using pre-trained Convolutional Neural Network (CNN) models, and employing typical ML approaches. Initially comprising eight classes, the dataset undergoes feature extraction using CNN algorithms, followed by the utilization of various feature selection methods such as Support Vector Classifier, Principal Component Analysis, Linear Discriminant Analysis, and optimization models like Particle Swarm Optimization, Bacterial Foraging Optimization, and Cat Swarm Optimization. In the final phase, seven conventional ML techniques are applied to classify the images of local fishes. Empirical measurements are gathered and analyzed to assess the proposed framework's performance. Particularly, the present approach achieves the highest accuracy of 98.71% through the utilization of the ML mechanism Logistic Regression with Resnet50, SVC, and CSO models.

Shaniff Esmail, Brendan Concannon

BackgroundImmersive virtual reality (VR) and artificial intelligence have been used to determine whether a simulated clinical exam setting can reduce anxiety in first-year occupational therapy students preparing for objective structured clinical examinations (OSCEs). Test anxiety is common among postsecondary students, leading to negative outcomes such as increased dropout risk, lower grades, and limited employment opportunities. Students unfamiliar with specific testing environments are particularly prone to anxiety. VR simulations of OSCEs may allow students to become familiar with the exam setting and reduce anxiety. ObjectiveThis study aimed to assess the efficacy of a VR simulation depicting clinical settings to reduce student anxiety about a clinical exam while gathering perspectives on their first-year coursework experiences to better understand their learning environment. MethodsAn experimental, nonrandomized controlled trial compared state anxiety, trait test anxiety, and OSCE grades in 2 groups of first-year occupational therapy students analyzed using independent t tests (2-tailed). Group 1 (NoVR) was not exposed to the VR simulation and acted as a control group for group 2 (YesVR), who were exposed to the VR simulation. The VR used artificial intelligence in the form of a generative pretrained transformer to generate responses from virtual patients as students interacted with them in natural language. Self-reported psychometric scales measured anxiety levels 3 days before the OSCE. YesVR students completed perceived preparation surveys at 2 time points—3 weeks and 3 days before the OSCE—analyzed using dependent t tests. Semistructured interviews and focus groups were conducted within 1 week after the OSCE. Student perspectives on their classes and VR experiences were summarized using interpretative thematic analysis. ResultsIn total, 60 students—32 (53%) in the NoVR group and 28 (47%) in the YesVR group—participated in the study, and the YesVR group showed a significant reduction in state anxiety (t58=3.96; P<.001; Cohen d=1.02). The mean difference was 11.96 units (95% CI 5.92-18.01). Trait test anxiety and OSCE scores remained static between groups. There was an increase in all perceived preparedness variables in the YesVR group. In total, 42% (25/60) of the participants took part in interviews and focus groups, providing major themes regarding factors that affect OSCE performance, including student experience and background, feedback and support, fear of unknown, self-consciousness, and knowledge of the exam environment. ConclusionsIntolerance of uncertainty may lead students to interpret ambiguous exam situations as overly precarious. Findings suggest that VR simulation was associated with reduced state anxiety, although results from this small, nonrandomized sample should be interpreted cautiously. Qualitative data indicated that VR helped students gain familiarity with clinical exam settings, potentially decreasing uncertainty-based anxiety. Future research with larger or randomized samples is needed to confirm these findings and explore advanced VR tools offering feedback to enhance learning.

Hassan Mishmast Nehi, Faranak Hosseinzadeh Saljooghi, Amir Rahimi et al.

Data Envelopment Analysis with inaccurate data poses a significant challenge in data science and analytics due to the inherent uncertainties and discrepancies present in real-world data. This article investigates the performance of units evaluated with inaccurate data and presents modeling approaches, including fuzzy and interval methodologies. In other words, by examining the effectiveness of units evaluated with interval data with fuzzy or interval-based bounds, novel approaches for modeling data coverage issues are introduced. Various mathematical techniques and analytical processes are utilized to solve problems and prove theorems. The primary focus is on modeling data coverage issues with fuzzy or interval bounds, which facilitates the creation of more accurate and effective representations of uncertain data. The findings of this article indicate that these modeling approaches lead to improvements in data-driven decision-making. Practical applications of these methods include information management and decision-making for DMU sets in fuzzy and interval environments, enabling analysts to make better decisions. This research contributes to advancing the field of data analytics by providing systematic methods for managing and analyzing inaccurate data, thereby enhancing the reliability and applicability of insights based on data foundations.

Rafiq Gheddar

As Islamic banks grow and evolve, pricing methods for their services have become essential to study and implement. This study highlights the significance of understanding the factors influencing Islamic banking service pricing in Algeria. The study aims to analyze how Islamic banks price their services, with a focus on cost, market, and value strategies. Additionally, it seeks to evaluate and recommend ways to enhance the current practices of banks operating in the national market. Algeria is experiencing rapid growth in Islamic banking, making it an ideal location to study this subject. The country is home to two Islamic banks, Al Baraka Bank and Al Salam Bank. Algeria was selected as a new market to allow the findings to be applicable to similar situations elsewhere. The research utilizes secondary data obtained from available information on Islamic bank service fees, comparing them with those of traditional banks. It also conducts financing simulations in both banks and compares them with the traditional theoretical framework. Data was gathered from various sources, including bank websites, annual reports, and previous studies. The research reveals that Algerian Islamic banks do not prioritize scientific methods in pricing their services. The results suggest that these banks operate within a traditional framework under the oversight of the central bank. The central bank's rules depend on the prices of services conventional banks offer. This shapes how customers perceive these banks as representatives of Islamic banking. Islamic banks can utilize the study's results to develop pricing strategies that are more effective and compliant with Islamic law. Regulators can utilize these findings to formulate enhanced policies to bolster the Islamic banking sector. The results also assist researchers in delving deeper into the realm of Islamic banking service pricing. This study refutes the hypothesis that Algerian Islamic banks have enhanced the efficiency of their service pricing by adopting models in line with Islamic finance principles, such as profit-sharing, while considering market conditions and service value. They should embrace more pragmatic and beneficial pricing strategies that align with Islamic law, cater to customer needs, and enhance their competitiveness and value in the national banking market.

Weidong WANG, Hui GAO, Xin SU et al.

For a multi-user integrated sensing and communication system in the network of vehicles, a robust sensing-assisted communication massive multiple-input multiple-output (MIMO) orthogonal time frequency space (OTFS) transmission scheme was proposed.Due to the limited sensing accuracy of the radar, errors existed in the channel state information (CSI) reconstructed based on sensing parameters.The transmission performance decreased as a result.To address this issue, the CSI in the delay doppler domain was reconstructed based on the sensing parameters by the transmitter firstly.And a robust beam forming scheme was designed considering the CSI error.Secondly, the channel estimation error and inter user interference were perceived by receivers based on sensing parameters.Then the robust receiver was designed by incorporating the perceived interference errors into the signal detector in an analytical way.Finally, numerical simulation results show that the proposed method effectively reduces the system bit error rate and increases the data reception rate of users.The proposed method improves the overall system performance in this situation.

Jiacheng XIE, Ziying ZHENG, Xuewen WANG et al.

The key to promoting intelligent construction is to integrate the digital twin technology form the operation mode of virtual and real integration. And the industrial metaverse based on digital twin is the future development direction of intelligent mining face. The concept of virtual and real integration operation mode of fully-mechanized mining face based on virtual reality-digital twin-cyber physical system-industrial metaverse is proposed. It has six connotation characteristics, such as display and off-line simulation, monitoring and auxiliary operation, online simulation and preview. It is an evolution process from low-level display simulation to high-level deep integration function. Finally, it have four abilities : the ability of reproduction mapping from real to virtual precision, the ability of reasoning and forecasting decision-making in virtual iteration, the ability of reproduction control from virtual to real, the ability of seamless cooperation between virtual and real human-computer, and the ability of lean management. The four capabilities of industrial metaverse and the key technologies to realize industrial metaverse are analyzed.Based on the existing monitoring, decision-making and control capabilities, AR remote assistance technology that can strengthen the cooperation ability between field operators and remote operators, robot cooperation technology that can strengthen the safety of operators, and virtual human technology that can use AI-driven operation in virtual space are integrated to build a hydraulic support adjusting experimental system based on industrial metaveise,and preliminary understanding of the application of industrial metaverse in coal mining.

Samuel David Vargas-Neira, Rodrigo Rodríguez-Cepeda

El presente artículo muestra los resultados de una intervención didáctica piloto, en la cual se diseñaron e implementaron algunos Trabajos Prácticos de Laboratorio (TPL) contextualizados, con el propósito de evaluar su incidencia en el aprendizaje significativo de parámetros fisicoquímicos de calidad en aceites comestibles. La intervención se realizó con un grupo de 14 estudiantes de ingeniería de alimentos, donde se analizaron las respuestas de los estudiantes a cuestionarios inicial y final, además de informes de trabajo práctico, desde un enfoque cualitativo. Se identificó que el diseño e implementación de TPL favorecen el aprendizaje significativo de los conceptos químicos asociados a la calidad de los aceites en los ingenieros en formación. En este sentido, los TPL fomentan criterios para evaluar la calidad de un producto en cuanto a aceptación o rechazo, lo cual permite desarrollar habilidades para la toma de decisiones.

Jan C. Brammer, Gerd Blanke, Claudia Kellner et al.

Abstract TUCAN is a canonical serialization format that is independent of domain-specific concepts of structure and bonding. The atomic number is the only chemical feature that is used to derive the TUCAN format. Other than that, the format is solely based on the molecular topology. Validation is reported on a manually curated test set of molecules as well as a library of non-chemical graphs. The serialization procedure generates a canonical “tuple-style” output which is bidirectional, allowing the TUCAN string to serve as both identifier and descriptor. Use of the Python NetworkX graph library facilitated a compact and easily extensible implementation. Graphical Abstract

Yanis Belkheyar, Joan Daemen, Christoph Dobraunig et al.

Recently, a memory safety concept called Cryptographic Capability Computing (C3) has been proposed. C3 is the first memory safety mechanism that works without requiring extra storage for metadata and hence, has the potential to significantly enhance the security of modern IT-systems at a rather low cost. To achieve this, C3 heavily relies on ultra-low-latency cryptographic primitives. However, the most crucial primitive required by C3 demands uncommon dimensions. To partially encrypt 64-bit pointers, a 24-bit tweakable block cipher with a 40-bit tweak is needed. The research on low-latency tweakable block ciphers with such small dimensions is not very mature. Therefore, designing such a cipher provides a great research challenge, which we take on with this paper. As a result, we present BipBip, a 24-bit tweakable block cipher with a 40-bit tweak that allows for ASIC implementations with a latency of 3 cycles at a 4.5 GHz clock frequency on a modern 10 nm CMOS technology.

Amirreza Asnafi, Mohsen Haji Zeinolabedini, Faezeh Ahmadipour

Access to the required information in all available scientific disciplines is one of the most important factors in the survival of that field. In the architecture field, the type of information format differs from other disciplines. The purpose of this study was to identify the behavior of images in the architecture of Shahid Beheshti University. The present study is an applied target and uses a descriptive survey method. The statistical population of the study consists of two groups of students and professors in the architecture major of Shahid Beheshti University. To determine the sample size, the Cochran formula was used and the sample size in this formula was 296 people. The results showed that the architects mainly used images for identifying creative ideas and taking advantage of the details of architectural structures. The type of image content they used was mostly photos, maps, and charts, which could be found in engines and image databases by limiting the size of the image and following related links as long as the image was taken. One of the major obstacles in finding images for architects was the lack of familiarity with the way they were searched. Creativity, proximity to the subject, credibility, and quality of the images were the criteria for selecting content. Considering the library's share in retrieving research-based images, it is suggested that library and library librarians conduct awareness-raising activities at the university's research groups such as brochures, conferences, library visits, and workshops.

Paul J. Reaidy, A. Gunasekaran, A. Spalanzani

Industrial deployment of the Internet Of Things (IOT) provides development of an ideal platform for decentralized management of warehouses. In this paper, we propose an IOT infrastructure for collaborative warehouse order fulfillment based on RFID, ambient intelligence and multi-agent system. It consists of a physical devices layer, a middleware ambient platform, a multi-agent system and an enterprise resource planning. It integrates a bottom-up approach with decision support mechanisms such as self-organization and negotiation protocols between agents based on "com-peration=competition+cooperation" concept. This approach was selected to improve reaction capabilities of decentralized management of warehouses in a dynamic environment. A collaborative warehouse example was conducted to demonstrate the implementation of the proposed infrastructure.

Borse Pranjal, Gaikwad Aishwarya, Dabhade Nachiket et al.

Nowadays, a large network of cameras is predominantly used in public places which provide enormous video data. These data are monitored manually and may be utilized only when the need arises to ascertain the facts. Automating the system can improve the quality of surveillance and be useful for high-level surveillance tasks like person identification, suspicious activity detection or undesirable event prediction for timely alerts. In this paper, we proposed a model that can Re-identify a person from a single camera tracking environment. This system will automatically extract face features of the person and generate the Unique Id for each person when it enters for the first time in the monitored area. Its face features are stored in the database which will help to Re-identify the person whenever the same person appears again. The challenges faced by the system are occlusion, pose, light conditions, and face orientation. The proposed system highlights, effect of different deep neural networks for Person Re-identification and compares based on the accuracy, GPU usage, Speed, Number of faces detected by overcoming the challenges like illumination and occlusion. The advantage of the system is it doesn′t require the database of people in advance for recognition and it will be helpful for criminal identification for crime control and prevention.

Vinay Kumar sharma, Anish Sachdeva, Lakhwinder Pal Singh

In recent times there is surge in the sustainable supply chain field. The focus of the present work is targeted towards viewing the major aspects of SSCM by focusing towards SSCM through the lens of meta-analysis by performing a structured literature review with the help of the already published articles available on SCOPUS database. A total of 369 articles have been identified from the database over a period of 15 years (2006-2020). The research articles chosen have been categorised and analysed in the viewpoint of journal wise, year wise, application wise, methodology, various barriers and drivers for SSCM. The study has enlightened on the key point of SSCM with the up-to-date developments, trends and the current scenarios. The research has shown that the multi criteria decision making techniques have been employed in abundance in the literature with a fair share of developing countries like India and China contributing into the field of study. This study is advantageous for both researchers and industry personnel for better understandings of SSCM.

Efthymios Constantinides

The paper assesses the current standing of the 4Ps Marketing Mix framework as the dominant marketing management paradigm and identifies market developments, environmental changes, and trends, as well as changing academic attitudes likely to affect the future of the Mix as theoretical concept and also the favourite management tool of marketing practitioners. It reviews the criticism on the 4P's emanating from five "traditional" marketing areas - Consumer Marketing, Relationship Marketing, Services Marketing, Retail Marketing, Industrial Marketing - and the emerging field of Electronic Marketing. The paper identifies two main limitations of the Marketing Mix as management tool, common in all examined domains, namely the model's internal orientation and lack of personalisation. It also identifies several area-specific limitations and underlines the need for further research on the issue. The weaknesses identified in the study seem to support the frequently expressed suggestion that marketing scholars should focus their efforts in formulating the conceptual foundations and marketing methodologies that better address the needs of today's and tomorrow's marketer.

D. Wren

D. Teece

I Nyoman Suamir, I Made Rasta

Chest freezer pada operasionalnya memerlukan beban transien yang fluktuatif dari waktu ke waktu sesuai dengan kondisi lingkungan. Untuk mampu memenuhi kebutuhan beban pendinginan maksimum, chest freezer umumnya dirancang dengan kapasitas lebih besar dari beban pendinginan yang dibutuhkan. Akibarnya sistem chest freezer kurang efisien dan kurang handal akibat sering mati-hidup selama operasi. Oleh karena itu perlu dikembangkan sistem chest freezer yang dapat mengurangi siklus mati-hidupnya kompresor dan menghemat penggunaan energi fosil. Penelitian ini mengkaji teknologi refrigerasi chest freezer dengan siklus kompresor yang kecil dan memiliki potensi untuk diintegrasikan dengan sumber energi terbarukan. Pendekatan teknologi yang diterapkan adalah teknologi chest freezer berbasis vegetable oil phase change materials (bio-PCM). Hasil investigasi menunjukkan bahwa penggunaan bio-PCM dapat menurunkan siklus kompresor dan mampu menjaga temperatur produk di bawah -15 derajat C. Konsumsi energi teknologi freezer yang diusulkan relatif sama dengan freezer tanpa bio-PCM. Tetapi bio-PCM dapat membuat chest freezer sangat potensial diintegrasikan dengan sumber energi surya.

C. Grönroos