An Anti-Cheating System for Online Interviews and Exams

Remote examination and job interviews have gained popularity and become indispensable because of both pandemics and the advantage of remote working circumstances. Most businesses and educational organizations use these platforms for recruitment as well as online exams. However, one of the critical problems of the remote examination systems is conducting the exams in a reliable environment. In this work, we present a cheating analysis pipeline for online interviews and exams. The system only requires a video of the candidate, which is recorded during the exam by using a webcam without a need for any extra tool. Then cheating detection pipeline is employed to detect the presence of another person, electronic device usage, and candidate absence status. The pipeline consists of face detection, face recognition, object detection, and face tracking algorithms. To evaluate the performance of the pipeline we collected a private video dataset. The video dataset includes both cheating activities and clean videos. Ultimately, our pipeline presents an efficient and fast guideline for detecting and analyzing cheating actions in an online interview and exam video

Assessing the supply chain performance: A causal analysis

Measuring the performance-related factors of a unit within a supply-chain is a challenging problem, mainly because of the complex interactions among the members governed by the supply chain strategy employed. Synergistic use of discrete-event simulation and structural equation modeling allows researchers and practitioners to analyze causal relationships between order-fulfillment characteristics of a supply-chain and retailers’ performance metrics. In this study, we model, simulate, and analyze a two-level supply-chain with seasonal linear demand, and using the information therein, develop a causal model to measure the links/relationships among the order-fulfillment factors and the retailer’s performance. According to the findings, of all the order-fulfillment characteristics of a supply-chain, the forecast inaccuracy was found to be the most important in mitigating the bullwhip effect. Concerning the total inventory cost and fill-rate as performance indicators of retailers, the desired service level had the highest priority, followed by the lead-time and forecast inaccuracy, respectively. To reduce the total inventory cost, the bullwhip effect seems to have the lowest priority for the retailers, as it does not appear to have a significant impact on the fill rate. Although seasonality (to some extent) influences the retailer’s performance, it does not seem to have a significant impact on the ranking of the factors affecting retailers’ supply-chain performance; except for the case where the backorder cost is overestimated.Q1WOS:0004961170000012-s2.0-8507513393

How do supply chain management and information systems practices influence operational performance?:Evidence from emerging country SMEs

This study first provides a comparative analysis of the impact of supply chain management (SCM) and information systems (IS) practices on operational performance (OPER) of small- and medium-sized enterprises (SMEs) operating in two neighbouring emerging country markets of Turkey and Bulgaria. Then, we investigate moderating effects of both SCM–IS-linked enablers and inhibitors on the links between SCM and IS practices and OPER of SMEs. To this end, we first empirically identify the underlying dimensions of SCM and IS practices, and SCM–IS-related enabling and inhibiting factors. Second, a series of regression analyses are undertaken to estimate the impact of the study's constructs on OPER of SMEs. The results are discussed comparatively within the contexts of both Turkish and Bulgarian SMEs and beyond. The study makes a significant contribution to the extant literature through obtaining and analysing cross-national survey data of SCM and IS practices in emerging country markets

Deadwood volume and quality in recreational forests: the case study of the Belgrade forest (Turkey)

Aim of the study: The aim of this study is to understand quantitative and qualitative characteristics of deadwood in recreational forests.Area of study: Belgrade forest in the North of Istanbul city (Turkey).Material and methods: The data has been collected through a stratified sampling scheme that has randomly located 50 clusters formed by 3 sample plots each (150 sample plots).Main results: The results show an average deadwood volume of 16.49 m3 ha-1 (81.5% in logs, 16.4% in snags, 2.1% in stumps). The highest volume of deadwood is in oldest forests (age over 180 years) with an average value of 20.39 m3 ha-1, followed by forests with 61-120 years with 15.77 m3 ha-1. Concerning forest management objectives, the results show that average deadwood volume is 13.66 m3 ha-1 in the forest section managed for water resource conservation and 21.14 m3 ha-1 in the forest section managed for recreational purposes.Research highlights: Deadwood management in the recreational forests must consider both biodiversity conservation and recreational attractiveness of an area.Keywords: forest management; forest types; forest accessibility; stand age; wood decomposition rate