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Marking their 50th Anniversary in the printing industry and the corporation’s 110th Anniversary in business, SHARP South Africa celebrated their success and unprecedented business growth during a partner event recently held in Johannesburg, South Africa. This event was a follow up from the Sharp summit in 2020 where representatives from SHARP Middle East & Africa [...]

The post SHARP announces Exceptional Performance and Launches its Future Workplace A3 MFPs appeared first on Braves News World.

Hanging onto the steering wheel for dear life while mumbling expletives is not what you imagine when you think of driving an S-Class. However, when it wears a ‘63’ badge, things are slightly different. More so when that badge gets red highlights, because that means the S-Class in question isn’t the usual, sophisticated, good boy, but its evil cousin. The Mercedes-AMG S 63 E-Performance is an 802hp limousine that is ready to rip a hole through time, and as its name suggests, it’s all about the performance. For once, the back seat takes a back seat in an S-Class. 

Mercedes-AMG S 63 powertrain and performance

The S 63 is a plug-in hybrid gone rogue. It gets a 4.0-litre twin-turbo V8, putting out 612hp and 900Nm, but then a 13kWh battery and electric motor on the rear axle put out an additional 190hp and 320Nm, bringing the total output to a hysterical 802hp and 1,430Nm. Deploying 1,430Nm of torque to the tarmac is like putting Usain Bolt on your home treadmill. There is so much grip that it feels like the car is trying to stretch the road beneath it every time you put your foot down. As a result, despite its 2.5-tonne heft, it can go from 0 to 100kph in just 3.4 seconds. The top speed is limited to 250kph, but if you opt for the Driver’s Pack, you can remove the limiter and get it up to 290kph. Clearly, range is not the priority for this hybrid. 

The numbers on the S 63 are intimidating, to say the least, and the experience from behind the wheel is, too. The car picks up the pace with zero lag, and you need to keep an eye on the speed readout; otherwise, it’s just a blur as you accelerate. 

What helps bring this earth-shattering performance to the road are two transmissions. The engine uses a speedshift 9-speed MCT, and the motor gets its own 2-speed transmission, because it spins at a different RPM from the engine. First gear on the motor is good enough for up to 140kph and only after that does it switch to second for a smoother torque transition. 

What you’ll be using most is the 9-speed with its paddle shifters. Needless to say, it is extremely responsive, and in Sport and Sport+, it’s extremely aggressive as well. When you push the car hard, shifts are immediate, and for total control, you can switch to ‘M’ or manual mode, where it will not upshift unless you tug at the right paddle. However, for everyday driving in the city, it isn’t the smoothest. There are noticeable jerks at low speeds, and even in Comfort mode, you’re constantly made aware of the massive power waiting to be unleashed. Then there is the exhaust, which, sadly, isn’t all-natural. A lot of it is fed through the speakers, and for the most part, you’ll barely hear it outside. Rev it high enough, though, and the V8 roar is very much there, along with pops and bangs that add to the drama. 

We’ve seen this powertrain in the GT 63 S E-Performance, where it had even more power (834hp) but a smaller (6.7kWh) battery. The S 63’s larger 13kWh battery results in a higher claimed electric-only range of 33km.  

Mercedes-AMG S 63 hybrid technology

The 13kWh battery pack uses Formula 1-derived tech and contains 1,200 individual cells that have a dedicated coolant line for thermal management. Not only is that better for packaging, but each cell can also be cooled individually, so you can push the car and not worry about overheating the battery. There are four recuperation modes—varying the level of regen—and you can charge the battery using a Type-2 port and the onboard 3.7kW AC charger. 

Exclusive to the S 63 is a ‘B’ or Battery Hold mode that helps preserve the SOC. This allows you to switch to the all-electric ‘EL’ mode in heavy traffic and save some precious high-octane fuel. 

Mercedes-AMG S 63 ride and handline

Because this is an AMG S-Class, there are two contrasting ideologies at work—sportscar handling and luxurious ride comfort. If you want S-Class levels of soft and supple, this won’t do the trick. The ride is inherently firm, and although it gets adaptive air suspension, you will feel jitters in the cabin even in Comfort mode. It also gets active engine mounts, which help keep things composed, and once you find a winding ribbon of tarmac with long swooping bends, the AMG side of the dynamic package is really felt. That said, on our bad roads, the one thing that you absolutely have to be aware of is the low ground clearance. Sure, the air suspension has a raise function that helps you gain some crucial millimetres, but you still have to crab crawl over big speed bumps to avoid grazing the underbody. 

In terms of handling, you don’t really expect big things from an S-Class, but AMG’s pedigree clearly flows through this car’s veins. The 4Matic+ system, along with 3-degree rear-wheel steering, makes a huge difference in the bends as well as in U-turns and three-point turns. Despite having the same long 3,216mm wheelbase as the standard S-Class, in the corners, it is agile and sharp. 

However, in seriously tight turns, its 2.5-tonne weight is what pulls it down, and at such points, all that handling tech can only do so much. 

Mercedes-AMG S 63 design

In terms of design, there are many telltale signs of it being an AMG. Edition 1 gets the ‘Night Pack’ that replaces every inch of bling with blackened bits and the ‘Carbon Pack’ that adds racy carbon-fibre elements to the air dams, splitter, side sill, mirrors and diffuser. Apart from that, it gets sporty bumpers with huge air dams, the massive ‘Panamericana’ grille and an AMG logo in place of the Mercedes-Benz emblem. There are also 21-inch wheels wrapped in Michelin Pilot Sport 4 tyres and carbon ceramic brakes (standard on the Edition 1).  

The rear, which many will find themselves looking at, features quad exhaust tips and red highlights for the badges, letting everyone know that this is an E-Performance and something that’s not to be trifled with. 

Mercedes-AMG S 63 interior and features

On the inside, the S 63 prides itself on its AMG roots with a healthy dose of carbon fibre. The dashboard gets a carbon-fibre slab with a red weave within. The upper half also gets red stitching along with Nappa leather seats, which, though sporty, are superbly comfy as well. The new bit is the performance steering wheel that gives it full-blown AMG cred. Wrapped in Alcantara and leather, its plethora of touch buttons might seem intimidating at first, but it doesn’t take long to get used to. The steering also features context-sensitive AMG knobs that feature shortcuts to adjust the suspension, gearbox, drive modes and even the exhaust. 

Also new are racier themes for the instrument cluster and telemetry, such as engine temperature, motor and battery readouts, and performance timing. The massive touchscreen in the centre is the nerve centre of the whole car, controlling everything from the AC to the chassis, and it’s super responsive. But rest assured, the screen has plenty of displays and data to satisfy your inner nerd.  

The rear seat may not be the best seat, given this is an AMG, but it’s always going to be special in an S-Class. You have plenty of room to stretch out, and all the bells and whistles like seat massaging, heating and ventilation, along with the ability to move the passenger seat ahead and fully stretch out.

There is a superb Burmester 4D sound system, panoramic sunroof, incredibly comfy seats, rear entertainment screens, and even noise-cancelling headphones if the V8 is not sonorous enough for you. That said, with all that carbon fibre surrounding you and the grin on your chauffeur’s face, it won’t be long before you want to jump back into the driver’s seat. Also, since the S 63’s hybrid tech sits over the rear axle, the boot space is down to 310 litres, and you don’t get a spare wheel either. 

Mercedes-AMG S 63 price

The S 63 E-Performance is priced from Rs 3.3 crore onwards, and the ‘Edition 1’ seen here, of which only three have been imported to India (and sold out), is listed at Rs 3.8 crore. It has supercar levels of power and all the luxury elements, and it is loaded with tech. Yet you’d struggle to justify the purchase. If you want a fun-to-drive car with lots of power, there are better options, and if you want a luxury car, the S-Class is already mighty impressive. It is difficult to see the logic, but as soon as you drive it, there is something about it that invokes your inner child. It won’t win track events or get you any drag race trophies. You won’t have a plausible justification. If you are the sort who looks for plausibility, this is definitely not the car for you. It’s a laugh, and you buy it because you can. If they ask you why you bought it, it’ll only take a quick spin to get them an answer. 

Also see: 

Mercedes India confirms over 12 new cars, SUVs coming this year

Next-gen Mercedes MB.EA Large EV platform cancelled amidst slow sales

Also see: 

Audi RS Q8 Performance revealed with 640hp

Mercedes-AMG has launched the new C 63 S E Performance in India at Rs 1.95 crore. The C 63 S E Performance marks AMG’s third new car launch this year and its third plug-in hybrid in India, following the S 63 E Performance and the GT 63 S E Performance. Bookings have opened today, and deliveries are expected from April 2025 onwards.

1. C 63 S E Performance pairs 476hp 4-cyl engine with 204hp motor
2. Gets sporty AMG-specific changes inside and outside
3. Buyers will get a complementary Nurburgring experience

Mercedes AMG C 63 S E Performance powertrain

Gone is the V8 engine that used to power the previous C 63. It’s been replaced with a 2.0-litre, four-cylinder, turbo-petrol engine that makes 476hp and 545Nm and is paired to a 9-speed automatic gearbox. The engine is paired to a rear axle-mounted electric motor that can put out a peak of 204hp and 320Nm. Total maximum output stands at 680hp and a whopping 1,020Nm of torque. Merc uses F1-derived tech for the turbocharger, which incorporates an electric motor that runs off the 400V electrical system, and helps the turbine spool faster.

Power is sent to all four wheels through the 4Matic+ system, which comes with a drift mode. The claimed 0-100kph time for the C 63 S E Performance is 3.4 seconds. The AMG Driver’s Package that's usually available as an option, is standard on the C 63. So top speed is 280kph.

The plug-in hybrid performance sedan gets a 6.1kWh battery pack (weighing 89kg), giving the C 63 an electric-only range of up to 13km. Four-wheel steering is also standard, which allows the rear wheels to turn up to 2.5deg in the opposite direction (up to 100kph), and up to 0.7deg in the same direction at speeds higher than that. The new C 63 gets eight drive modes – Electric, Comfort, Battery Hold, Sport, Sport+, RACE, Slippery and Individual – along three levels for its adaptive damping system – Comfort, Sport, and Sport+.

Mercedes AMG C 63 S E Performance interior, exterior

Compared to the standard C-Class, the AMG-spec model gets a vertically slatted grille with active shutters that open or close depending on the engine’s cooling needs. The restyled, more aggressive front and rear bumper increase the car's length by 83mm, and the wider front wheel arches make the performance version 76mm wider than the standard sedan. Lightweight 20-inch alloy wheels are standard.

Mercedes says AMG exclusive paint options like the Matt Graphite Grey Magno are customisable, and optional ceramic high-performance composite brakes can be specced instead of the standard ventilated and perforated metal ones. Naturally, the company offers a great deal of personalisation options with the C 63 S E Performance.

On the inside, the AMG and the standard model share the same layout, but this gets an all-black theme and an AMG-specific steering wheel. The ventilated sports seats in nappa leather and carbon fibre interior trim, a 12.3-inch touchscreen infotainment and head-up display, and the 710W, 15-speaker Burmester sound system are standard. AMG Performance seats are an optional extra. Along with the usual list of ADAS features, 7 airbags and a 360-degree camera are standard fit.

Mercedes-AMG says that every buyer of the C 63 S E Performance will get a complementary opportunity to race at the Nürburgring.

Mercedes AMG C 63 S E Performance price, rivals

While the Rs 1.95 crore Mercedes-AMG C 63 S E Performance has no direct rivals in India, other models that vie in this rarefied performance-focused space include the recently launched 550hp BMW M4 CS (Rs 1.89 crore) and the larger 500hp Porsche Panamera GTS (Rs 2.34 crore).

All prices, ex-showroom, India

Also see:

2024 Mercedes-AMG G 63 video review

Mercedes-AMG confirms future electric super SUV

11th edition of Mercedes-Benz Classic Car Rally slated for November 24

As urbanisation accelerates, India risks surpassing global benchmarks for energy efficiency and carbon emissions in buildings. In such a scenario, HPBs offer resilience through adaptive, self-sufficient structures. They promote social well-being by nurturing healthier indoor environments, including air quality

Mercedes-Benz India has introduced the Mercedes-AMG C 63 S E PERFORMANCE, a hybrid sports sedan that blends high-performance engineering with Formula 1™-inspired technology

This Luckeep X2 Stormtrooper E-Bike is Awesome We’ve tested a lot of electric bikes. I like some for certain reasons, others for other reasons, and some I really don’t care for much at all. I have to say that one thing I’ve found over the years is that e-bikes seem ... [continued]

The post Exploring the Luckeep X2: A High-Performance Urban E-Bike for All Terrains appeared first on CleanTechnica.

Fredrica discusses the ethical problems of enhancing performance with medication.

TCP BBR is one of the most powerful congestion control algorithms. In this article, we provide a comprehensive review of BBR analysis, expanding on existing knowledge across various fronts. Utilising ns3 simulations, we evaluate BBR's performance under diverse conditions, generating graphical representations. Our findings reveal flaws in the probe's RTT phase duration estimation and unequal bandwidth sharing between BBR and CUBIC protocols. Specifically, we demonstrated that the probe's RTT phase duration estimation algorithm is flawed and that BBR and CUBIC generally do not share bandwidth equally. Towards the end of the article, we propose a new improved version of TCP BBR which minimises these problems of inequity in bandwidth sharing and corrects the inaccuracies of the two key parameters RTprop and cwnd. Consequently, the BBR' protocol maintains very good fairness with the Cubic protocol, with an index that is almost equal to 0.98, and an equity index over 0.95.

A number of studies have applied social network analysis (SNA) to show that the patterns of social interaction between software developers explain important organisational outcomes. However, these insights are based on a single network relation (i.e., uniplex social ties) between software developers and do not consider the multiple network relations (i.e., multiplex social ties) that truly exist among project members. This study reassesses the understanding of software developer networks and what it means for performance in software development settings. A systematic review of SNA studies between 1990 and 2020 across six digital libraries within the IS and management science domain was conducted. The central contributions of this paper are an in-depth overview of SNA studies to date and the establishment of a research agenda to advance our knowledge of the concept of multiplexity on how a multiplex perspective can contribute to a software developer's coordination of tasks and performance advantages.

Pandemic has compelled the entire world to change their way of life and work. To control the infection rate, academic institutes deliver education online similarly. At least one smartphone is available in every home, and students use their smartphones to attend class. The study investigates the link between smartphone usage (SU) and academic performance (AP) during the pandemic. 490 data were obtained from various institutions and undergraduate students using stratified random sampling. These components were identified using factor analysis and descriptive methods, while the relationship of SU and AP based on gender classification was tested using Smart-PLS-SEM. The findings show that SU has a substantial relationship with academic success, whether done in class or outside of it. Even yet, the study found that SU and AP significantly impact both male and female students. Furthermore, the research focuses on SU outside and within the classroom to improve students' AP.

Prior work demonstrates the importance of introducing young children to programming and engineering content before gender stereotypes are fully developed and ingrained in later years. However, very little research on gender and early childhood technology interventions exist. This pilot study looks at N=45 children in kindergarten through second grade who completed an eight-week robotics and programming curriculum using the KIWI robotics kit. KIWI is a developmentally appropriate robotics construction set specifically designed for use with children ages 4 to 7 years old. Qualitative pre-interviews were administered to determine whether participating children had any gender-biased attitudes toward robotics and other engineering tools prior to using KIWI in their classrooms. Post-tests were administered upon completion of the curriculum to determine if any gender differences in achievement were present. Results showed that young children were beginning to form opinions about which technologies and tools would be better suited for boys and girls. While there were no significant differences between boys and girls on the robotics and simple programming tasks, boys performed significantly better than girls on the advanced programming tasks such as, using repeat loops with sensor parameters. Implications for the design of new technological tools and curriculum that are appealing to boys and girls are discussed.

Aim/Purpose: Compared student academic performance on specific course requirements in a C# programming course across three instructional approaches: traditional, online, and flipped. Background: Addressed the following research question: When compared to the online and traditional instructional approaches, does the flipped instructional approach have a greater impact on student academic performance with specific course requirements in a C# programming course? Methodology: Quantitative research design conducted over eight 16-week semesters among a total of 271 participants who were undergraduate students en-rolled in a C# programming course. Data collected were grades earned from specific course requirements and were analyzed with the nonparametric Kruskal Wallis H-Test using IBM SPSS Statistics, Version 23. Contribution: Provides empirical findings related to the impact that different instructional approaches have on student academic performance in a C# programming course. Also describes implications and recommendations for instructors of programming courses regarding instructional approaches that facilitate active learning, student engagement, and self-regulation. Findings: Resulted in four statistically significant findings, indicating that the online and flipped instructional approaches had a greater impact on student academic performance than the traditional approach. Recommendations for Practitioners: Implement instructional approaches such as online, flipped, or blended which foster active learning, student engagement, and self-regulation to increase student academic performance. Recommendation for Researchers: Build upon this study and others similar to it to include factors such as gender, age, ethnicity, and previous academic history. Impact on Society: Acknowledge the growing influence of technology on society as a whole. Higher education coursework and programs are evolving to encompass more digitally-based learning contexts, thus compelling faculty to utilize instructional approaches beyond the traditional, lecture-based approach. Future Research: Increase the number of participants in the flipped instructional approach to see if it has a greater impact on student academic performance. Include factors beyond student academic performance to include gender, age, ethnicity, and previous academic history.

Aim/Purpose: The goal of this paper is to examine whether having female robotics teachers positively impacts girls’ performance on programming and robotics tasks Background: Women continue to be underrepresented in the technical STEM fields such as engineering and computer science. New programs and initiatives are needed to engage girls in STEM beginning in early childhood. The goal of this work is to explore the impact of teacher gender on young children’s mastery of programming concepts after completing an introductory robotics program. Methodology: A sample of N=105 children from six classrooms (2 Kindergarten, 2 first grade, and 2 second grade classes) from a public school in Somerville, Massachusetts, participated in this research. Children were taught the same robotics curriculum by either an all-male or all-female teaching team. Upon completion of the curriculum, they completed programming knowledge assessments called Solve-Its. Comparisons between the performance of boys and girls in each of the teaching groups were made. Findings: This paper provides preliminary evidence that having a female instructor may positively impact girls’ performance on certain programming tasks and reduce the number of gender differences between boys and girls in their mastery of programming concepts. Recommendations for Practitioners: Practitioners should expose children to STEM role-models from a variety of backgrounds, genders, ethnicities, and experiences. Future Research: Researchers should conduct future studies with larger samples of teachers in order to replicate the findings here. Additionally, future research should focus on collecting data from teachers in the form of interviews and surveys in order to find out more about gender-based differences in teaching style and mentorship and the impact of this on girls' interest and performance in STEM.

Aim/Purpose: One of the main objectives of higher education institutions is to provide a high-quality education to their students and reduce dropout rates. This can be achieved by predicting students’ academic achievement early using Educational Data Mining (EDM). This study aims to predict students’ final grades and identify honorary students at an early stage. Background: EDM research has emerged as an exciting research area, which can unfold valuable knowledge from educational databases for many purposes, such as identifying the dropouts and students who need special attention and discovering honorary students for allocating scholarships. Methodology: In this work, we have collected 300 undergraduate students’ records from three departments of a Computer and Information Science College at a university located in Saudi Arabia. We compared the performance of six data mining methods in predicting academic achievement. Those methods are C4.5, Simple CART, LADTree, Naïve Bayes, Bayes Net with ADTree, and Random Forest. Contribution: We tested the significance of correlation attribute predictors using four different methods. We found 9 out of 18 proposed features with a significant correlation for predicting students’ academic achievement after their 4th semester. Those features are student GPA during the first four semesters, the number of failed courses during the first four semesters, and the grades of three core courses, i.e., database fundamentals, programming language (1), and computer network fundamentals. Findings: The empirical results show the following: (i) the main features that can predict students’ academic achievement are the student GPA during the first four semesters, the number of failed courses during the first four semesters, and the grades of three core courses; (ii) Naïve Bayes classifier performed better than Tree-based Models in predicting students’ academic achievement in general, however, Random Forest outperformed Naïve Bayes in predicting honorary students; (iii) English language skills do not play an essential role in students’ success at the college of Computer and Information Sciences; and (iv) studying an orientation year does not contribute to students’ success. Recommendations for Practitioners: We would recommend instructors to consider using EDM in predicting students’ academic achievement and benefit from that in customizing students’ learning experience based on their different needs. Recommendation for Researchers: We would highly endorse that researchers apply more EDM studies across various universities and compare between them. For example, future research could investigate the effects of offering tutoring sessions for students who fail core courses in their first semesters, examine the role of language skills in social science programs, and examine the role of the orientation year in other programs. Impact on Society: The prediction of academic performance can help both teachers and students in many ways. It also enables the early discovery of honorary students. Thus, well-deserved opportunities can be offered; for example, scholarships, internships, and workshops. It can also help identify students who require special attention to take an appropriate intervention at the earliest stage possible. Moreover, instructors can be aware of each student’s capability and customize the teaching tasks based on students’ needs. Future Research: For future work, the experiment can be repeated with a larger dataset. It could also be extended with more distinctive attributes to reach more accurate results that are useful for improving the students’ learning outcomes. Moreover, experiments could be done using other data mining algorithms to get a broader approach and more valuable and accurate outputs.

This study aims to examine the intellectual capital and its effect on the financial performance of Ethiopian private commercial banks using the pulic model. Quantitative panel data from audited annual reports of Ethiopian private commercial banks from 2011 to 2019 are collected. The robust fixed effect regression model has been adopted to investigate the effect of IC and the financial performance measures of the banks. The study results show a positive relationship between the value added intellectual coefficient (VAIC) and the financial performance of private commercial banks in Ethiopia. The study also revealed that the components of VAIC (i.e., human capital efficiency, capital employed efficiency, and structural capital efficiency) have a positive and significant effect on the financial performance of banks measured by return on asset and return on equity over the study periods. Practically, the results of the study could be useful for shareholders to consider IC as a strategic resource and hence emphasise these intangibles, and to the bank managers to benchmark themselves against the best competitors based on the level of efficiency rankings.

The present study is a modest attempt to investigate the impact of gender diversity on firm performance of BSE 200 listed companies. The study is based on the secondary data collected from the EMIS database and the corporate governance reports for a period of eight years, i.e., from 2012 to 2019. Sample size of the present study is 174 Indian companies listed in the Bombay Stock Exchange. The study has employed multiple regression models by considering the endogeneity issue to empirically test the impact of gender diversity on firm performance in Indian context. Based on the multiple regression models, we find that the impact of gender diversity is positive and significant on the market-based measure of firm performance. However, the impact becomes negative significant when firm performance was measured by accounting based measure of firm performance.

Corporate social responsibility (CSR) and sustainability are gaining worldwide recognition. The question of whether CSR and sustainability programs benefit an organisation's financial success is still being debated. This study aims to verify this phenomenon by examining the current literature pattern on this relationship using bibliometric and systematic review analysis. It further provides a taxonomy for understanding this association. VOSviewer is used to obtain comprehensive dataset mapping and clustering in the field. The manuscript offers promising insights regarding academia by assessing the pattern of publication trends, the most influential author in the area, and analysing the methodological and theoretical underpinnings of CSR, sustainability and firm performance linkage. The outcome of this study provides exploratory insights into research gaps and avenues for future research.

In several manufacturing firms, inventory constitutes most of the current assets, and this underscores the importance of inventory management as a fundamental issue for the majority of the firms irrespective of their sizes. Therefore, the purpose of this research is to assess the factors that influence the effectiveness of inventory management of Malaysian SMEs in the manufacturing sector. The study employs PLS-SEM technique to test the hypotheses. The main findings show that documentation and records, inventory control system and qualified personnel have positive effects on effective inventory management of Malaysian SMEs in the manufacturing sector. The study also reveals that effective inventory management has a mediating effect on the relationship between documentation and records, inventory control system, qualified personnel and organisational performance. Therefore, the study recommends that Malaysian SMEs in the manufacturing sector should improve their approaches to embracing effective inventory management practices in order to enhance organisational performance.

This research investigates the correlation between risk management and supply chain performance (SCP) along with moderation of AI-embedded technologies such as big data analytics, Internet of Things (IoT), virtual reality, and blockchain technologies. To calculate the results, this study utilised 644 questionnaires through the structural equation modelling (SEM) method. It is revealed using SmartPls that financial risk management (FRM) is positively linked with SCP. Second, it was observed that AI significantly moderates the connection between FRM and SCP. In addition, the study presents certain insights into supply chain and AI-enabled technologies and how these capabilities can beneficially advance SCP. Besides, certain implications, both managerial and theoretical are described for the supply chain managers along with limitations for future scholars of the world.

With the rapid development of Artificial Intelligence (AI) technology, significant breakthroughs have been made in its application in many fields. Especially, in the field of enterprise human resource management and employee performance evaluation, AI has demonstrated its powerful ability to optimise and improve performance. This study explores the application of AI in enterprise human resource management and how to use AI to evaluate employee performance. The research includes analysing and comparing existing AI-driven human resource management models, evaluating how AI can help improve employee performance and leadership styles, and designing and developing human resource management computer systems for enterprise employees. Through empirical research and case analysis, this study proposes a new AI-optimised employee performance evaluation model and explores its application and effect in practice. In general, the application of AI can improve the efficiency and accuracy of enterprise human resource management, and provide new possibilities for employee performance evaluation. At present, artificial intelligence technology has been widely used in various fields of daily life, especially in corporate human resource management, providing better support for the development of enterprises.

The research goal is to solve the problems of low accuracy and long time existing in traditional teaching reform performance evaluation methods, a performance evaluation method of teaching reform based on hierarchical multi-task deep learning is proposed. Under the principle of constructing the evaluation index system, the evaluation indicator system should be constructed. The weight of the evaluation index is calculated through the analytic hierarchy process, and the calculation result of the evaluation weight is taken as the model input sample. A hierarchical multi-task deep learning model for teaching reform performance evaluation is built, and the final teaching reform performance score is obtained. Through relevant experiments, it is proved that compared with the experimental comparison method, this method has the advantages of high evaluation accuracy and short time, and can be further applied in relevant fields.

Multi-criteria inventory classification (MCIC) is popularly used to aid managers in categorising the inventory. Researchers have used numerous mathematical models and approaches, but few resorted to unsupervised machine-learning techniques to address MCIC. This study uses the expectation-maximisation (EM) algorithm to estimate the parameters of the Gaussian mixture model (GMM), a popular unsupervised machine learning algorithm, for ABC inventory classification. The EM-GMM algorithm is sensitive to initialisation, which in turn affects the results. To address this issue, two different initialisation procedures have been proposed for the EM-GMM algorithm. Inventory classification outcomes from 14 existing MCIC models have been given as inputs to study the significance of the two proposed initialisation procedures of the EM-GMM algorithm. The effectiveness of these initialisation procedures corresponding to various inputs has been analysed toward inventory management performance measures, i.e., fill rate, total relevant cost, and inventory turnover ratio.

Simulations have been shown to be an effective tool in traditional learning environments; however, as distance learning grows in popularity, the need to examine simulation effectiveness in this environment has become paramount. A casual-comparative design was chosen for this study to determine whether students using a computer-based instructional simulation in hybrid and fully online environments learned better than traditional classroom learners. The study spans a period of 6 years beginning fall 2008 through spring 2014. The population studied was 281 undergraduate business students self-enrolled in a 200-level microcomputer application course. The overall results support previous studies in that computer simulations are most effective when used as a supplement to face-to-face lectures and in hybrid environments.

This longitudinal, quasi-experimental study investigated students’ cognitive personality type using the Myers-Briggs personality Type Indicator (MBTI) in Internet-based Online and Face-to-Face (F2F) modalities. A total of 1154 students enrolled in 28 Online and 32 F2F sections taught concurrently over a period of fourteen years. The study measured whether the sample is similar to the national average percentage frequency of all 16 different personality types; whether specific personality type students preferred a specific modality of instructions and if this preference changed over time; whether learning occurred in both class modalities; and whether specific personality type students learned more from a specific modality. Data was analyzed using regression, t-test, frequency, and Chi-Squared. The study concluded that data used in the study was similar to the national statistics; that no major differences in preference occurred over time; and that learning did occur in all modalities, with more statistically significant learning found in the Online modality versus F2F for Sensing, Thinking, and Perceiving types. Finally, Sensing and Thinking (ST) and Sensing and Perceiving (SP) group types learned significantly more in Online modality versus F2F.

The authors present the results of a study conducted at a comprehensive, urban, coeducational, land-grant university. A quasi-experimental design was chosen for this study to compare student performance in two different classroom environments, traditional versus flipped. The study spanned 3 years, beginning fall 2012 through spring 2015. The participants included 433 declared business majors who self-enrolled in several sections of the Management Information Systems course during the study. The results of the current study mirrored those of previous works as the instructional method impacted students’ final grade. Thus, reporting that the flipped classroom approach offers flexibility with no loss of performance when compared to traditional lecture-based environments.

Aim/Purpose: The purpose of this study was to examine whether grit was a contributing factor to student persistence and success at minority serving institutions. Background: A number of studies conducted in the past fifteen years have concluded that grit is a positive predictor of achievement across many domains. But, is grit really the ultimate panacea for student success? This longitudinal study sought to answer that question by specifically focusing on business students attending a mid-Atlantic minority-serving institution that primarily serves low-income and first generation learners. Methodology: The research study under consideration used quantitative methods for data collection and analysis. It was initiated in the Fall of 2014 with the administration of the standard 12-item Grit assessment to all freshmen students enrolled in a university business department. Students were then followed longitudinally over a five year period with GPA and persistence to graduation documented. During the analyses, grit score was compared to participant first year GPA’s as well as retention and persistence to graduation via comparison tables and ANOVAs. Contribution: A lack of substantive studies conducted at HBCUs and other minority serving institutions poses a major gap in the existing literature available on grit. A number of authors have put forth a call to action for faculty at minority serving institutions to conduct meaningful studies focused on grit and student persistence in order to better inform the HBCU community. This study is specifically purposed to help fill some of the gaps in the available literature. The results of the research presented in this paper hopefully shed light on the need to explore non-cognitive factors that may affect student performance. In particular, research should explore factors that may, or may not, contribute to the success of under prepared college students in particular those who are from low income, first generation, and minority groups. This form of exploration is part of a commitment to positive student outcomes. Findings: According to the findings, there is a significant positive correlation between higher grit scores and both GPA and persistence to graduation. First year GPA, however, was not found to be a reliable predictor of academic success. Recommendations for Practitioners: As part of a commitment to positive student outcomes, faculty and administrators in higher education must be constantly exploring factors that may, or may not, impact student success. Recommendation for Researchers: The results of this research help to shed light on the need to explore elements that may help to contribute to the success of under prepared college students in particular those who are from low income, first generation, and minority groups Future Research: The authors conclude that while building the grittiness of freshmen students may lead to positive student outcomes, grit alone might not be enough. In fact, they postulate that grittiness without clarity of purpose, positive self-efficacy, and growth mindset may mean that students who may be gritty may not be exerting their energies appropriately. During the next phase, a model that is currently under development will be used as part of a mindset intervention to edify students about grit, growth mindset, locus of control/self-efficacy, and clarity of purpose. A complimentary research study examining student performance and perceptions will also be conducted.