Search results for: business intelligence

Authors: Triza Edwar Fawzi Deif

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In the process of urbanization in China, new rural construction is on the ascendant, which is becoming more and more popular. Under the driving effect of rural urbanization, the house pattern and tectonic methods of traditional vernacular houses have shown great differences from the family structure and values of contemporary peasant families. Therefore, it is particularly important to find a prototype, form and strategy to make a balance between the traditional memory and modern functional requirements. In order for research to combine the regional culture with modern life, under the situation of the current batch production of new rural residences, Badie village, in Zhejiang province, is taken as the case. This paper aims to put forward a prototype which can not only meet the demand of modern life but also ensure the continuation of traditional culture and historical context for the new rural dwellings design. This research not only helps to extend the local context in the construction of the new site but also contributes to the fusion of old and new rural dwellings in the old site construction. Through the study and research of this case, the research methodology and results can be drawn as reference for the new rural construction in other areas.

Keywords: steel slag, co-product, primary coating, steel aggregate capital, rural areas, rural planning, rural governance village, design strategy, new rural dwellings, regional context, regional expression

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Authors: C. Li, G. Coates, N. Johnson, M. Mc Guinness

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In the UK, flooding is responsible for significant losses to the economy due to the impact on businesses, the vast majority of which are Small and Medium Enterprises (SMEs). Businesses of this nature tend to lack formal plans to aid their response to and recovery from disruptive events such as flooding. This paper reports on work on how an agent-based model (ABM) is being developed based on interview data gathered from SMEs at-risk of flooding and/or have direct experience of flooding. The ABM will enable simulations to be performed allowing investigations of different response strategies which SMEs may employ to lessen the impact of flooding, thus strengthening their resilience.

Keywords: ABM, flood response, SMEs, business continuity

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Authors: Akram Waheb Nasef Alzordoky

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The wars and armed conflicts have frequently ended in violations of global humanitarian law and regularly devote the maximum severe global crimes, which include war crimes, crimes towards humanity, aggression and genocide. But, simplest inside the XX century, the guideline changed into an articulated idea of establishing a frame of worldwide criminal justice so that you can prosecute those crimes and their perpetrators. The first steps on this subject were made with the aid of setting up the worldwide army tribunals for warfare crimes at Nuremberg and Tokyo, and the formation of ad hoc tribunals for the former Yugoslavia and Rwanda. Ultimately, the global criminal courtroom was established in Rome in 1998 with the aim of justice and that allows you to give satisfaction to the sufferers of crimes and their families. The aim of the paper was to provide an ancient and comparative analysis of the establishments of worldwide criminal justice primarily based on which those establishments de lege lata fulfilled the goals of individual criminal responsibility and justice. Moreover, the authors endorse de lege ferenda that the everlasting global crook Tribunal, in addition to the potential case, additionally takes over the current ICTY and ICTR cases.

Keywords: social networks privacy issues, social networks security issues, social networks privacy precautions measures, social networks security precautions measures

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Authors: Olga Shvetsova

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The research paper contains the different issues of competence management in innovation companies. The theoretical bases of human resources management and practical issues of innovative enterprises’ competitiveness are considered. The research is focused on the modern innovative enterprise management problems; it focuses on the effective management of the personnel of innovative enterprises on the basis of competence approach. The concept of core competence approach is discussed. The point of view, that the key competences of the company create the competitive advantages, support strategy development and protect business from external negative factors is considered. The used methodology is background research.

Keywords: competence model, competitiveness, innovation management, implementation

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Authors: Seong Jun Yoon, Jasurbek Doliev, Sang Min Oh, Rodi Hartono, Kyoojae Shin

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Electric power steering (EPS), which is commonly used in electric vehicles recently, is an electric-driven steering device for vehicles. Compared to hydraulic systems, EPS offers advantages such as simple system components, easy maintenance, and improved steering performance. However, because the EPS system is a nonlinear model, difficult problems arise in controller design. To address these, various machine learning and artificial intelligence approaches, notably artificial neural networks (ANN), have been applied. ANN can effectively determine relationships between inputs and outputs in a data-driven manner. This research explores two main areas: designing an EPS identifier using an ANN-based backpropagation (BP) algorithm and enhancing the EPS system controller with an ANN-based Levenberg-Marquardt (LM) algorithm. The proposed ANN-based BP algorithm shows superior performance and accuracy compared to linear transfer function estimators, while the LM algorithm offers better input angle reference tracking and faster response times than traditional PID controllers. Overall, the proposed ANN methods demonstrate significant promise in improving EPS system performance.

Keywords: ANN backpropagation modelling, electric power steering, transfer function estimator, electrical vehicle driving system

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Authors: Laura Simmer, Maria Kalt, Oliver Schauer

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Freight transport is growing fast, but many vehicles are empty or just partially loaded. The vision and concepts of the Physical Internet (PI) proposes to eliminate these inefficiencies. Aiming for a radical sustainability improvement, the PI – inspired by the Digital Internet – is a hyperconnected global logistic system, enabling seamless asset sharing and flow consolidation. The implementation of a PI in its full expression will be a huge challenge: the industry needs innovation and implementation support including change management approaches, awareness creation and good practices diffusion, legislative actions to remove antitrust and international commerce barriers, standardization and public incentives policies. In order to take a step closer to this future the project ‘Atropine - Fast Track to the Physical Internet’ funded under the Strategic Economic and Research Program ‘Innovative Upper Austria 2020’ was set up. The two-year research project unites several research partners in this field, but also industrial partners and logistics service providers. With Atropine, the consortium wants to actively shape the mobility landscape in Upper Austria and make an innovative contribution to an energy-efficient, environmentally sound and sustainable development in the transport area. This paper should, on the one hand, clarify the questions what the project Atropine is about and, on the other hand, how a proof of concept will be reached. Awareness building plays an important role in the project as the PI requires a reorganization of the supply chain and the design of completely new forms of inter-company co-operation. New business models have to be developed and should be verified by simulation. After the simulation process one of these business models will be chosen and tested in real life with the partner companies. The developed results - simulation model and demonstrator - are used to determine how the concept of the PI can be applied in Upper Austria. Atropine shall pave the way for a full-scale development of the PI vision in the next few decades and provide the basis for pushing the industry toward a new level of co-operation with more shared resources and increased standardization.

Keywords: Atropine, inter-company co-operation, Physical Internet, shared resources, sustainable logistics

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Authors: Musatafa Abbas Abbood Albadr, Masri Ayob, Sabrina Tiun, Fahad Taha Al-Dhief, Mohammad Kamrul Hasan

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Breast Cancer (BC) is considered one of the most frequent reasons of cancer death in women between 40 to 55 ages. The BC is diagnosed by using digital images of the FNA (Fine Needle Aspirate) for both benign and malignant tumors of the breast mass. Therefore, this work proposes the Online Sequential Extreme Learning Machine (OSELM) algorithm for diagnosing BC by using the tumor features of the breast mass. The current work has used the Wisconsin Diagnosis Breast Cancer (WDBC) dataset, which contains 569 samples (i.e., 357 samples for benign class and 212 samples for malignant class). Further, numerous measurements of assessment were used in order to evaluate the proposed OSELM algorithm, such as specificity, precision, F-measure, accuracy, G-mean, MCC, and recall. According to the outcomes of the experiment, the highest performance of the proposed OSELM was accomplished with 97.66% accuracy, 98.39% recall, 95.31% precision, 97.25% specificity, 96.83% F-measure, 95.00% MCC, and 96.84% G-Mean. The proposed OSELM algorithm demonstrates promising results in diagnosing BC. Besides, the performance of the proposed OSELM algorithm was superior to all its comparatives with respect to the rate of classification.

Keywords: breast cancer, machine learning, online sequential extreme learning machine, artificial intelligence

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Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

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Authors: Antonyous Fawzy Boshra Girgis

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Nutrition labels are diet-related health policies. They help individuals improve food-choice decisions and reduce intake of calories and unhealthy food elements, like cholesterol. However, many individuals do not pay attention to nutrition labels or fail to appropriately understand them. According to the literature, thinking and cognitive styles can have significant effects on attention to nutrition labels. According to the author's knowledge, the effect of global/local processing on attention to nutrition labels has not been previously studied. Global/local processing encourages individuals to attend to the whole/specific parts of an object and can have a significant impact on people's visual attention. In this study, this effect was examined with an experimental design using the eye-tracking technique. The research hypothesis was that individuals with local processing would pay more attention to nutrition labels, including nutrition tables and traffic lights. An experiment was designed with two conditions: global and local information processing. Forty participants were randomly assigned to either global or local conditions, and their processing style was manipulated accordingly. Results supported the hypothesis for nutrition tables but not for traffic lights.

Keywords: nutrition, public health, SA Harvest, foodeye-tracking, nutrition labelling, global/local information processing, individual differencesmobile computing, cloud computing, nutrition label use, nutrition management, barcode scanning

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Authors: Birce Boga Bakirli

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In this paper, we investigate ideas on human capital development and management in industries. We structured a model to be able to gather the data from the interviews conducted with worker, specialists and owners of companies. Different aspects of the situation are found in these interviews, and we used the information to model the benefit of the business owners and workers perspectives. These are modelled as a bi-level programming problem. Several instances of the generic cases are solved. The results show the importance of education within and out of the company for workers, and it returns for the company.

Keywords: bi-level programming, corporate strategy, cost tradeoffs, human capital, mixed integer programming, Stackelberg game, supplier relations, strategic planning

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Authors: Ogunrinde Roseline Bosede, Ogunrinde Rowland Rotimi

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Just as the development of ideas of early mathematics was essentially motivated by social needs, the invention of the computer was equally inspired by social needs. The early years of the twenty-first century have been remarkable in advances in mathematical and computer sciences. Mathematical and computer sciences work are fast becoming an increasingly integral and essential components of a growing catalogues of areas of interests in biology, business, military, medicine, social sciences, advanced design, advanced materials, climate, banking and finance, and many other fields of disciplines. This paper seeks to highlight the trend and impacts of the duo in the technological advancements being witnessed in our today's world.

Keywords: computer, impacts, mathematics, modern society

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Authors: Hamidreza Fallah Lajimi, Elham Karami, Alireza Arab, Fatemeh Alinasab

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Being responsive is an increasingly important skill for firms in today’s global economy; thus firms must be agile. Naturally, it follows that an organization’s agility depends on its supply chain being agile. However, achieving supply chain agility is a function of other abilities within the organization. This paper analyses results from a survey of 71 Iran manufacturing companies in order to identify some of the factors for agile organizations in managing their supply chains. Then we classification this company in four cluster with fuzzy c-mean technique and with Four validations functional determine automatically the optimal number of clusters.

Keywords: agile supply chain, clustering, fuzzy clustering, business engineering

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Authors: James Forren

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This research paper details a recent demonstrator project in which digital form found textile structures were built by human craftspersons wearing augmented reality (AR) head-worn displays (HWDs). The project utilized a wet-state natural fiber / cementitious matrix composite to generate minimal bending shapes in tension which, when cured and rotated, performed as minimal-bending compression members. The significance of the project is that it synthesizes computational structural simulations with visually guided handcraft production. Computational and physical form-finding methods with textiles are well characterized in the development of architectural form. One difficulty, however, is physically building computer simulations: often requiring complicated digital fabrication workflows. However, AR HWDs have been used to build a complex digital form from bricks, wood, plastic, and steel without digital fabrication devices. These projects utilize, instead, the tacit knowledge motor schema of the human craftsperson. Computational simulations offer unprecedented speed and performance in solving complex structural problems. Human craftspersons possess highly efficient complex spatial reasoning motor schemas. And textiles offer efficient form-generating possibilities for individual structural members and overall structural forms. This project proposes that the synthesis of these three modalities of structural problem-solving – computational, human, and material - may not only develop efficient structural form but offer further creative potentialities when the respective intelligence of each modality is productively leveraged. The project methodology pertains to its three modalities of production: 1) computational, 2) human, and 3) material. A proprietary three-dimensional graphic statics simulator generated a three-legged arch as a wireframe model. This wireframe was discretized into nine modules, three modules per leg. Each module was modeled as a woven matrix of one-inch diameter chords. And each woven matrix was transmitted to a holographic engine running on HWDs. Craftspersons wearing the HWDs then wove wet cementitious chords within a simple falsework frame to match the minimal bending form displayed in front of them. Once the woven components cured, they were demounted from the frame. The components were then assembled into a full structure using the holographically displayed computational model as a guide. The assembled structure was approximately eighteen feet in diameter and ten feet in height and matched the holographic model to under an inch of tolerance. The construction validated the computational simulation of the minimal bending form as it was dimensionally stable for a ten-day period, after which it was disassembled. The demonstrator illustrated the facility with which computationally derived, a structurally stable form could be achieved by the holographically guided, complex three-dimensional motor schema of the human craftsperson. However, the workflow traveled unidirectionally from computer to human to material: failing to fully leverage the intelligence of each modality. Subsequent research – a workshop testing human interaction with a physics engine simulation of string networks; and research on the use of HWDs to capture hand gestures in weaving seeks to develop further interactivity with rope and chord towards a bi-directional workflow within full-scale building environments.

Keywords: augmented reality, cementitious composites, computational form finding, textile structures

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Authors: Aya Salama

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Digital Twin is an emerging research topic that attracted researchers in the last decade. It is used in many fields, such as smart manufacturing and smart healthcare because it saves time and money. It is usually related to other technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, Human digital twin (HDT), in specific, is still a novel idea that still needs to prove its feasibility. HDT expands the idea of Digital Twin to human beings, which are living beings and different from the inanimate physical entities. The goal of this research was to create a Human digital twin that is responsible for real-time human replies automation by simulating human behavior. For this reason, clustering, supervised classification, topic extraction, and sentiment analysis were studied in this paper. The feasibility of the HDT for personal replies generation on social messaging applications was proved in this work. The overall accuracy of the proposed approach in this paper was 63% which is a very promising result that can open the way for researchers to expand the idea of HDT. This was achieved by using Random Forest for clustering the question data base and matching new questions. K-nearest neighbor was also applied for sentiment analysis.

Keywords: human digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification, clustering

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Authors: Ahmet Sekreter

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Although there are conceptual similarities in terms of financial products between conventional and Islamic finance, they are entirely different financial systems. Despite Islamic finance’s small size in the conventional finance world, its promising growth makes Islamic finance a hot topic both in academia and business world. Today customers can access sophisticated Islamic financial products not only in Muslim countries but also in Europe. This study analyzes Islamic finance and its products and includes a brief overview of Islamic finance in Europe. Literature review is the basis of this paper. The author analyzed the academic papers, numerical data, and estimations to set a perspective for the future of Islamic finance in Europe. Findings show that UK is the main hub for the Islamic finance, and it will remain so in the near future.

Keywords: islamic finance, islamic banking, islamic finance in Europe, finance

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Authors: Muhammad Fathurridho

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Grammar as a rule used by every language to be understood by everyone is always related to syntax and morphology. Arabic grammar is different with another languages’ grammars. It has more rules and difficulties. This paper aims to investigate and describe the English grammatical errors of machine translation systems in translating Arabic sentences, including declarative, exclamation, imperative, and interrogative sentences, specifically in year 2018 which can be supported with artificial intelligence’s role. The Arabic sample sentences which are divided into two; verbal and nominal sentence of several Arabic published texts will be examined as the source language samples. The translated sentences done by several popular online machine translation systems, including Google Translate, Microsoft Bing, Babylon, Facebook, Hellotalk, Worldlingo, Yandex Translate, and Tradukka Translate are the material objects of this research. Descriptive method that will be taken to finish this research will show the grammatical errors of English target language, and classify them. The conclusion of this paper has showed that the grammatical errors of machine translation results are varied and generally classified into morphological, syntactical, and semantic errors in all type of Arabic words (Noun, Verb, and Particle), and it will be one of the evaluations for machine translation’s providers to correct them in order to improve their understandable results.

Keywords: Arabic, Arabic-English translation, machine translation, grammatical errors

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Authors: Zeinab Hmama

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Much recent discourse has highlighted the supporting role of social entrepreneurs in solving social problems. However, the identification of social enterprise’s characteristics in emerging countries has not yet been thoroughly examined. This research seeks to explores the profile of social enterprises in Morocco. In this perspective, we conduct a quantitative study on a sample of 87 social enterprises. This study was undertaken in Morocco based on a quantitative study lead among sample consists of 82 organizations qualified as social enterprises. Therefore, the response rate was 45.12% (37/82). Participants in the study were described on the basis of the following demographic characteristics: Gender, Age, Education Level and field, Entrepreneurial activity age, Legal forms, Line of business.

Keywords: social entrepreneurship, social enterprise, problem resolution, value creation

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Authors: Muller Salah Zaky Toudry

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The complexity arises in defining the development great due to its notion, based on inherent market situations and their requirements, the diverse stakeholders itself and their desired output. An quantitative survey based totally approach was adopted in this optimistic examine. A questionnaire-primarily based survey was performed for the assessment of production fine belief and expectations within the context of excellent development technique. The survey feedback of experts of the leading creation corporations/companies of Pakistan production industry have been analyzed. The monetary ability, organizational shape, and production revel in of the construction companies shaped basis for their selection. The great belief become located to be venture-scope-orientated and taken into consideration as an extra cost for a production assignment. Any excellent improvement technique changed into expected to maximize the profit for the employer, via enhancing the productiveness in a creation project. The look at is beneficial for the construction specialists to evaluate the prevailing creation great perception and the expectations from implementation of any pleasant improvement approach in production projects.

Keywords: correlation analysis, lean construction tools, lean construction, logistic regression analysis, risk management, safety construction quality, expectation, improvement, perception client loyalty, NPS, pre-construction, schedule reduction

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Authors: Sohail Imran, Tariq Mahmood

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In complex healthcare diagnostic investigation process, medical practitioners have to focus on ways to standardize their processes to perform high quality care and optimize the time and costs. Process mining techniques can be applied to extract process related knowledge from data without considering causal and dynamic dependencies in business domain and processes. The application of process mining is effective in diagnostic investigation. It is very helpful where a treatment gives no dispositive evidence favoring it. In this paper, we applied process mining to discover important process flow of diagnostic investigation for hepatitis patients. This approach has some benefits which can enhance the quality and efficiency of diagnostic investigation processes.

Keywords: process mining, healthcare, diagnostic investigation process, process flow

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Authors: K. Volkonitskaya, S. Lyapina

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According to the National Monitoring Centre of innovation infrastructure, scientific and technical activities and regional innovation systems by December 2014. 166 technology parks were established in Russia. Comparative analysis of technological parks performance in Russia, the USA, Israel and the European Union countries revealed significant reduction of key performance indicators in Russian innovation infrastructure institutes. The largest deviations were determined in the following indicators: new products and services launched, number of companies and jobs, amount of venture capital invested. Lower performance indicators of Russian technology parks can be partly explained by slack demand for national high-tech products and services, lack of qualified specialists in the sphere of innovation management and insufficient cooperation between different innovation infrastructure institutes. In spite of all constraints in innovation segment of Russian economy in 2010-2012 private investors for the first time proceeded to finance building of technological parks. The general purpose of the research is to answer two questions: why despite the significant investment risks private investors continue to implement such comprehensive infrastructure projects in Russia and is business model of private technological park more efficient than strategies of state innovation infrastructure institutes? The goal of the research was achieved by analyzing business models of private technological parks in Moscow, Kaliningrad, Astrakhan and Kazan. The research was conducted in two stages: the on-line survey of key performance indicators of private and state Russian technological parks and in-depth interviews with top managers and investors, who have already build private technological parks in by 2014 or are going to complete investment stage in 2014-2016. The results anticipated are intended to identify the reasons of efficient and inefficient technological parks performance. Furthermore, recommendations for improving the efficiency of state technological and industrial parks were formulated. Particularly, the recommendations affect the following issues: networking with other infrastructural institutes, services and infrastructure provided, mechanisms of public-private partnership and investment attraction. In general intensive study of private technological parks performance and development of effective mechanisms of state support can have a positive impact on the growth rates of the number of Russian technological, industrial and science parks.

Keywords: innovation development, innovation infrastructure, private technology park, public-private partnership

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Authors: Samuel Nii Tackie, Oyebade K. Oyedotun, Ebenezer O. Olaniyi, Adnan Khashman

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Artificial neural networks have been used in different fields of artificial intelligence, and more specifically in machine learning. Although, other machine learning options are feasible in most situations, but the ease with which neural networks lend themselves to different problems which include pattern recognition, image compression, classification, computer vision, regression etc. has earned it a remarkable place in the machine learning field. This research exploits neural networks as a data mining tool in predicting the number of times a student repeats a course, considering some attributes relating to the course itself, the teacher, and the particular student. Neural networks were used in this work to map the relationship between some attributes related to students’ course assessment and the number of times a student will possibly repeat a course before he passes. It is the hope that the possibility to predict students’ performance from such complex relationships can help facilitate the fine-tuning of academic systems and policies implemented in learning environments. To validate the power of neural networks in data mining, Turkish students’ performance database has been used; feedforward and radial basis function networks were trained for this task; and the performances obtained from these networks evaluated in consideration of achieved recognition rates and training time.

Keywords: artificial neural network, data mining, classification, students’ evaluation

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Authors: Ogola Lois Kange

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The study looked at the role technology had previously played and now plays in small and medium scale women-owned businesses starting up in Kaduna, which is an emerging entrepreneurship hub state in Nigeria. The study selected a random population of 20 businesses drawn from the north and south of Kaduna. The selection was based on a survey administered to 100 Women-owned businesses that had started up within the last 3-5years. Questionnaires were administered and analyzed based on the participants’ backgrounds, upbringing, exposure and access to technology. One of the key findings is that women-owned businesses can no longer thrive without the application of basic technology.

Keywords: business, entrepreneurship, start-up, technology, women

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Authors: Ahmed Krobba, Meriem Touzene, Mohamed Debeyche

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The wireless communications system (5G) will provide more diverse applications and higher quality services for users compared to the long-term evolution 4G (LTE). 5G uses a higher carrier frequency, which suffers from information loss in 5G coverage. Most 5G users often cannot obtain high-quality communications due to transmission channel noise and channel complexity. Physical Uplink Control Channel (PUCCH-NR: Physical Uplink Control Channel New Radio) plays a crucial role in 5G NR telecommunication technology, which is mainly used to transmit link control information uplink (UCI: Uplink Control Information. This study based of evaluating the performance of channel physical uplink control PUCCH-NR under low Signal-to-Noise Ratios with various antenna numbers reception. We propose the artificial intelligence approach based on deep neural networks (Deep Learning) to estimate the PUCCH-NR channel in comparison with this approach with different conventional methods such as least-square (LS) and minimum-mean-square-error (MMSE). To evaluate the channel performance we use the block error rate (BLER) as an evaluation criterion of the communication system. The results show that the deep neural networks method gives best performance compared with MMSE and LS

Keywords: 5G network, uplink (Uplink), PUCCH channel, NR-PUCCH channel, deep learning

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Authors: Abrar Abuzaid, Maha Alaaeddine, Haya Alesayi

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This project is centered around understanding the usage and impact of Alexa, Amazon's popular virtual assistant, in everyday life. Alexa, known for its integration into devices like Amazon Echo, offers functionalities such as voice interaction, media control, providing real-time information, and managing smart home devices. Our primary focus is to conduct a straightforward survey aimed at uncovering how people use Alexa in their daily routines. We plan to reach out to a wide range of individuals to get a diverse perspective on how Alexa is being utilized for various tasks, the frequency and context of its use, and the overall user experience. The survey will explore the most common uses of Alexa, its impact on daily life, features that users find most beneficial, and improvements they are looking for. This project is not just about collecting data but also about understanding the real-world applications of a technology like Alexa and how it fits into different lifestyles. By examining the responses, we aim to gain a practical understanding of Alexa's role in homes and possibly in workplaces. This project will provide insights into user satisfaction and areas where Alexa could be enhanced to meet the evolving needs of its users. It’s a step towards connecting technology with everyday life, making it more accessible and user-friendly

Keywords: Amazon Alexa, artificial intelligence, smart speaker, natural language processing

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Authors: Xinchao Liu

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Regulating environmental and human rights damages caused by transnational corporations in host States is a core issue in the business and human rights discourse. In current regulatory practices, host States, which are territorially based and should bear primary regulation responsibility, face dual challenges at both domestic and international levels, leading to their continued marginalization. Specifically, host States as TNC damage regulators are constrained domestically by territorial jurisdiction limitations and internationally by the neoliberal international economic order exemplified by investment protection mechanisms. Taking China as a sample, it currently lacks a comprehensive regulation system to address TNC damages; while domestic constraints manifest as the marginalization of judicial regulation, the absence of corporate duty of care, and inadequate extraterritorial regulation effectiveness, international constraints are reflected in the absence of foreign investor obligations in investment agreements and the asymmetry of dispute resolution clauses, challenging regulatory sovereignty. As China continues to advance its policy of high-quality opening up, the risks of negative externalities from transnational capital will continue to increase, necessitating a focus on building and perfecting a regulation mechanism for TNC damages within the framework of international law. To address domestic constraints, it is essential to clarify the division of regulation responsibilities between judicial and administrative bodies, promote the normalization of judicial regulation, and enhance judicial oversight of governmental settlements. Improving the choice of law rules for cross-border torts and the standards for parent company liability for omissions, and enhancing extraterritorial judicial effectiveness through transnational judicial dialogue and cooperation mechanisms are also crucial. To counteract international constraints, specifying investor obligations in investment treaties and designing symmetrical dispute resolution clauses are indispensable to eliminate regulatory chill. Additionally, actively advancing the implementation of TNC obligations in business and human rights treaty negotiations will lay an international legal foundation for the regulation sovereignty of host States.

Keywords: transnational corporate damages, home state litigation, optimization limit, investor-state dispute settlement

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Authors: H. D. Arora, Anjali Dhiman

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Uncertainty is found everywhere and its understanding is central to decision making. Uncertainty emerges as one has less information than the total information required describing a system and its environment. Uncertainty and information are so closely associated that the information provided by an experiment for example, is equal to the amount of uncertainty removed. It may be pertinent to point out that uncertainty manifests itself in several forms and various kinds of uncertainties may arise from random fluctuations, incomplete information, imprecise perception, vagueness etc. For instance, one encounters uncertainty due to vagueness in communication through natural language. Uncertainty in this sense is represented by fuzziness resulting from imprecision of meaning of a concept expressed by linguistic terms. Fuzzy set concept provides an appropriate mathematical framework for dealing with the vagueness. Both information theory, proposed by Shannon (1948) and fuzzy set theory given by Zadeh (1965) plays an important role in human intelligence and various practical problems such as image segmentation, medical diagnosis etc. Numerous approaches and theories dealing with inaccuracy and uncertainty have been proposed by different researcher. In the present communication, we generalize fuzzy entropy proposed by De Luca and Termini (1972) corresponding to Shannon entropy(1948). Further, some of the basic properties of the proposed measure were examined. We also applied the proposed measure to the real life decision making problem.

Keywords: entropy, fuzzy sets, fuzzy entropy, generalized fuzzy entropy, decision making

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Authors: Krisztina Szegedi, Gyula Fülöp, Ádám Bereczk

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The shared goal of social entrepreneurship, corporate social responsibility and social innovation is the advancement of society. The business model of social enterprises is characterized by unique strategies based on the competencies of the entrepreneurs, and is not aimed primarily at the maximization of profits, but rather at carrying out goals for the benefit of society. Corporate social responsibility refers to the active behavior of a company, by which it can create new solutions to meet the needs of society, either on its own or in cooperation with other social stakeholders. The objectives of this article are to define concepts, describe and integrate relevant theoretical models, develop a model and introduce some examples of international practice that can inspire initiatives for social development.

Keywords: corporate social responsibility, CSR, social innovation, social entrepreneurship

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Authors: Ruchi Agarwal

Abstract:

In today’s world, companies are operating in dynamic, uncertain and ambiguous business environments. Globally, more companies are failing due to Environmental, Social and Governance (ESG) factors than ever. Corporate governance and risk management are intertwined in nature. For decades, corporate governance and risk management have been influenced by internal and external factors. Three schools of thought have influenced risk governance for decades: Agency theory, Contingency theory, and Institutional theory. Agency theory argues that agents have interests conflicting with principal interests and the information problem. Contingency theory suggests that risk management adoption is influenced by internal and external factors, while Institutional theory suggests that organizations legitimize risk management with regulators, competitors, and professional bodies. The conflicting objectives of theories have created problems for executives in organizations in the adoption of Risk Governance. So far, there are many studies that discussed risk culture and the role of actors in risk governance, but there are rare studies discussing the role of risk culture in the adoption of risk governance from a leadership style perspective. This study explores the adoption of risk governance in two contrasting industries, such as the Insurance and energy business, to understand whether risk governance is influenced by internal/external factors or whether risk culture is influenced by leaders. We draw empirical evidence by comparing the cases of an Indian insurance company and a renewable energy-based firm in India. We interviewed more than 20 senior executives of companies and collected annual reports, risk management policies, and more than 10 PPTs and other reports from 2017 to 2024. We visited the company for follow-up questions several times. The findings of my research revealed that both companies have used risk governance for strategic renewal of the company. Insurance companies use a transactional leadership style based on performance and reward for improving risk, while energy companies use rather symbolic management to make debt restructuring meaningful for stakeholders. Overall, both companies turned from loss-making to profitable ones in a few years. This comparative study highlights the role of different leadership styles in the adoption of risk governance. The study is also distinct as previous research rarely studied risk governance in two contrasting industries in reference to leadership styles.

Keywords: leadership style, corporate governance, risk management, risk culture, strategic renewal

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Authors: Shelley Harrington

Abstract:

As a result of increasingly dynamic business environments, the creation and fostering of dynamic capabilities, [those capabilities that enable sustained competitive success despite of dynamism through the awareness and reconfiguration of internal and external competencies], supported by organisational learning [a dynamic capability] has gained increased and prevalent momentum in the research arena. Presenting findings funded by the Economic Social Research Council, this paper investigates the extent to which Senior Management Team (SMT) personality (at the trait and facet level) is associated with the creation of dynamic managerial capabilities at the team level, and effective organisational learning/knowledge sharing within the firm. In doing so, this research highlights the importance of micro-foundations in organisational psychology and specifically dynamic capabilities, a field which to date has largely ignored the importance of psychology in understanding these important and necessary capabilities. Using a direct measure of personality (NEO PI-3) at the trait and facet level across 32 high technology and finance firms in the UK, their CEOs (N=32) and their complete SMTs [N=212], a new measure of dynamic managerial capabilities at the team level was created and statistically validated for use within the work. A quantitative methodology was employed with regression and gap analysis being used to show the empirical foundations of personality being positioned as a micro-foundation of dynamic capabilities. The results of this study found that personality homogeneity within the SMT was required to strengthen the dynamic managerial capabilities of sensing, seizing and transforming, something which was required to reflect strong organisational learning at middle management level [N=533]. In particular, it was found that the greater the difference [t-score gaps] between the personality profiles of a Chief Executive Officer (CEO) and their complete, collective SMT, the lower the resulting self-reported nature of dynamic managerial capabilities. For example; the larger the difference between a CEOs level of dutifulness, a facet contributing to the definition of conscientiousness, and their SMT’s level of dutifulness, the lower the reported level of transforming, a capability fundamental to strategic change in a dynamic business environment. This in turn directly questions recent trends, particularly in upper echelons research highlighting the need for heterogeneity within teams. In doing so, it successfully positions personality as a micro-foundation of dynamic capabilities, thus contributing to recent discussions from within the strategic management field calling for the need to empirically explore dynamic capabilities at such a level.

Keywords: dynamic managerial capabilities, senior management teams, personality, dynamism

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Authors: Shinoy Vengaramkode Bhaskaran, Kaushik Sathupadi, Sandesh Achar

Abstract:

Human locomotion recognition is important in a variety of sectors, such as robotics, security, healthcare, fitness tracking and cloud computing. With the increasing pervasiveness of peripheral devices, particularly Inertial Measurement Units (IMUs) sensors, researchers have attempted to exploit these advancements in order to precisely and efficiently identify and categorize human activities. This research paper introduces a state-of-the-art methodology for the recognition of human locomotion patterns in a cloud environment. The methodology is based on a publicly available benchmark dataset. The investigation implements a denoising and windowing strategy to deal with the unprocessed data. Next, feature extraction is adopted to abstract the main cues from the data. The SelectKBest strategy is used to abstract optimal features from the data. Furthermore, state-of-the-art ML classifiers are used to evaluate the performance of the system, including logistic regression, random forest, gradient boosting and SVM have been investigated to accomplish precise locomotion classification. Finally, a detailed comparative analysis of results is presented to reveal the performance of recognition models.

Keywords: artificial intelligence, cloud computing, IoT, human locomotion, gradient boosting, random forest, neural networks, body-worn sensors

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